diff --git a/.nojekyll b/.nojekyll new file mode 100644 index 00000000..e69de29b diff --git a/about/index.html b/about/index.html new file mode 100644 index 00000000..b76d1f49 --- /dev/null +++ b/about/index.html @@ -0,0 +1,316 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + About + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Intelligent Systems Phystech +
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+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Department of Intelligent Systems

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Phystech School of Applied Mathematics and Informatics MIPT

+ +

The base department graduates bachelors and masters in the direction 010900 “Applied Mathematics and Physics”. Education at the department is in three specializations “Data Science”, “Design and Organization of Intelligent Systems”, “Information Retrieval and Machine Learning”. The base organization is the Computing Center of the Federal Research Center “Informatics and Control” of the Russian Academy of Sciences.

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The base organization is the Computing Center of the Russian Academy of Sciences, the Federal Research Center “Informatics and Control” of the Russian Academy of Sciences. The founder is an academician of the Russian Academy of Sciences and an outstanding Russian mathematician, an expert in the field of mathematical methods of recognition, forecasting and data analysis Konstantin Vladimirovich Rudakov. The department has been actively developing since 2003 within the scientific school of the academician of the Russian Academy of Sciences Yuri Ivanovich Zhuravlev. A significant contribution to the development of the department was made by the professor of the Russian Academy of Sciences, Doctors of Physical and Mathematical Sciences. K.V. Vorontsov and V.V. Strijov.

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Teachers of the department

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20 researchers: professor of the Russian Academy of Sciences, doctors and candidates of sciences. Teachers are young candidates of sciences, graduates of the department Ph.D. Alexander Aduenko, Ph.D. Oleg Bakhteev, Ph.D. Roman Isachenko, graduate student Andrey Grabovoy. The average age of the teachers is 35 years.

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Areas of educational and scientific activities of the department

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Machine learning; multivariate statistics; geometric methods of deep learning; model selection and neural network architectures; ensembles of models and generative neural networks; functional data analysis and analysis of spatio-temporal data.

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Applied Research

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Text analysis and topic modeling, image and video analysis, multivariate time series analysis, biomedical signal analysis, brain-computer interfaces.

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Principles of Scientific Work

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Openness of ideas, projects, results at all stages of study and research; continuous assessment of the quality of ideas and results; communication with the scientific community, updating according to the latest achievements.

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Main courses

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Machine Learning, read by K.V. Vorontsov, is the most famous and complete course in Russia, covering fundamental and modern topics of machine learning and data analysis.

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My first scientific article: automation of scientific research, read by V.V. Strijov, is a course that provides the basics for performing scientific research - from planning to presenting results. Each student chooses a personal project and receives a personal consultant and expert. For three months, the student prepares a scientific paper with theory and computational experiment. The results are presented at scientific conferences, articles are submitted to peer-reviewed journals.

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Main courses (programs)

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Scholarships

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Collaborative training programs

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In 2019, the department organized a double degree and joint master’s program at the University of Grenoble-Alpes. Master’s students study in joint programs at the Paris Polytechnic School, the Skolkovo Institute of Science and Technology, the KAUST University of Science and Technology. Joint research is underway with laboratories UGA, INRIA, CNRS, Ecole Polytechnique, EPFL, Los-Alamos, CMU.

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Internships

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Since the beginning, the department has been actively cooperating with the base companies of the Forexis Group of Companies: Forexis, Antiplagiat, Antirutina, GoodfoCast, Labor Laboratory, Procompliance and participates in joint projects of Forexis Group with the companies MMFB, InterRAO, Yandex, Sberbank, Russian Railways, Samsung, LG.

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Come and study with us and do research on machine learning!

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+ + diff --git a/admission/index.html b/admission/index.html new file mode 100644 index 00000000..8f914ef8 --- /dev/null +++ b/admission/index.html @@ -0,0 +1,302 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Admission + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Intelligent Systems Phystech +
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+ + Machine Learning
+ + Data Analysis
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Admission format: interview

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Algorithm of admission, bachelors, 2nd year:

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  1. A student fills in the form,
    2. +
  2. solves one of the following tasks,
    3. +
  3. makes an opinion about the work performed by the students of the department,
    4. +
  4. on the appointed date, makes a three-minute report on the task and on the topic or work of interest,
    5. +
  5. is waiting for the decision of the dean’s office on the distribution to the department.
    6. +
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The interview procedure from the point of view of the department teachers:

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1.Gathering the whole group of those wishing to enter the department,

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    +
  1. Listen to a short report of each participant, +
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    • “solving a test problem”,
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    • “my goals for admission to the department” on the material of student works of the department,
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    +
    2. +
  2. Ask questions, look at the questionnaire,
    3. +
  3. Draw up a ranked list of applicants, publish [by the link here] and send it to the dean’s office, close the reception.
    4. +
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The Master admission procedure:

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    +
  1. A student fills the form,
    2. +
  2. sends a request to mlalgorithms at gmail
    3. +
  3. parts interview with +
      +
    • BS thesis,
      • +
    • topics and results of the students scientific works at the department,
      • +
    • mathematics of the BS programme: algebra, analysis, probability (functional analysis and measure theory included)
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    +
    4. +
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Test problems (2022 and earlier)

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Link – the spring of 2023 will be published here

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Check the your basic abilities, spring 2023

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Chapters 1, 2, 3 from the Pen and Paper Exercises in Machine Learning by Michael U. Gutmann

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Tips for solving problems (these are just tips, not directions)

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Report topics for discussion

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Link

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+ + diff --git a/course/automation_scientific_research/index.html b/course/automation_scientific_research/index.html new file mode 100644 index 00000000..fbc11705 --- /dev/null +++ b/course/automation_scientific_research/index.html @@ -0,0 +1,376 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Automation of Scientific Research + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Intelligent Systems Phystech +
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+ + Machine Learning
+ + Data Analysis
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Automation of Scientific Research

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About (My first scientific paper)

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This course produces student research papers. It gathers research teams in a society. Each team combines a student, a consultant and an expert. The student is a project driver, who wants to plunge into scientific research activities. The consultant, a graduated student, conducts the research and helps the student. The expert, a professor, states the problem and enlightens the road to the goal.

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Link ko course page

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Syllabus

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Labworks

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A selected project on applied mathematics or machine learning, conducted by a consultant and professor. The delivery is a paper, a code and a talk.

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Grading

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Each week carries several tasks. Each task brings one point exactly according to the schedule of the course.

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Prerequisites

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Algebra and analysis at the third year of undergraduate level.

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Lecturers

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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + Vadim Strijov +

+
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+ + diff --git a/course/bayesian_model_selection/index.html b/course/bayesian_model_selection/index.html new file mode 100644 index 00000000..95ee4864 --- /dev/null +++ b/course/bayesian_model_selection/index.html @@ -0,0 +1,373 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Bayesian Model Selection + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + +
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+ +
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+ Intelligent Systems Phystech +
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+ + Machine Learning
+ + Data Analysis
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Bayesian Model Selection

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About

+

The course is dedicated to the basis of Bayesian Methods in Machine Learning, Bayesian Models’ construction and inference. The notion of optimal bayesian forecast is introduced, and the methods for constructing the one are studied. The methods for handling non-linearities and inhomogeneities in data are discussed. Handling of missing data and optimal model evolution with time are considered from a Bayesian perspective.

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Syllabus

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Labworks

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4 theoretical tasks (performed individually), 1 practical task and 1 competition (performed in teams), 2 tests. +Written and oral exam (the latter can be substituted by the presentation on a selected topic).

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Grading

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Each theoretical task gives at most 50 / 100 points, while practical one and competition each give up to 50 points. The score for the TOP1 student in each task is doubled (extra points). Written and oral exams add up to 250 together. +The final mark is computed by scaling the total score by maximal one assuming no extra points gained.

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Prerequisites

+

Probability, Basic Machine Learning, Linear Algebra, Optimization.

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Lecturers

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+ +
+ + + + +
+

+ + + + Aleksander Aduenko +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + diff --git a/course/bayesian_multimodeling/index.html b/course/bayesian_multimodeling/index.html new file mode 100644 index 00000000..b055cbfe --- /dev/null +++ b/course/bayesian_multimodeling/index.html @@ -0,0 +1,358 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Bayesian Multimodeling + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Bayesian Multimodeling

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+ + + + + +
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About

+

The course is devoted to the problem of optimal model selection in machine learning and data analysis tasks. During the course, we investigate the Bayesian approach to model selection, its theoretical and practical aspects. We consider properties of model selection methods both specific to some notable model families or general properties suitable for the most model families.

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Syllabus

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The course investigates the properties of model selection for different types of models: from linear to mixtures of experts built on deep learning models. Various approaches to model selection and hyperparameter optimization are discussed, including gradient-based methods, sequential model based optimization methods, methods based on hypernetworks and supernetworks.

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Labworks

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4 practical homeworks and 2 oral talks (optional) every term. There is also a simple questionnaire after each pair.

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Grading

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The overall score is a sum of scores for practical tasks, talks and the answers for the questionnaire.

+ +

Prerequisites

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Statistics, linear algebra, machine learning, deep learning, intro to bayesian inference.

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+

Lecturers

+
+ +
+ + + + + + + + +
+

+ + + + Oleg Bakhteev +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + diff --git a/course/bioinformatics/index.html b/course/bioinformatics/index.html new file mode 100644 index 00000000..a96fd53c --- /dev/null +++ b/course/bioinformatics/index.html @@ -0,0 +1,373 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Bioinformatics + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + +
+ +
+
+ +
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+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Bioinformatics

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About

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In the course of lectures, unique features of biological data are considered, leading to original statements of recognition and classification problems. It should be noted that for almost all the problems considered in the course, accurate and mathematically sound solutions have not yet been proposed. In this sense, the course represents an extensive field of activity for independent scientific work of students. +A system of recognition tasks is formulated that reflects the structure of biological systems and provides a basis for the construction of problem-oriented theories. The fundamentals of the formalism developed to solve the problems of bioinformatics and other poorly formalized problems in the field of advanced biomedical research and sentiment analysis are considered. This formalism is based on the theory of universal and local constraints within the framework of an algebraic approach to recognition. Attention is paid to biomedical applications of the results of intelligent analysis of biological data.

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Syllabus

+ + +

Labworks

+

Practical tasks will be announced during the lectures. Students can formulate the topics of research tasks themselves. After selecting the task, the work requirements are discussed.

+ +

Grading

+

Before the start of the oral exam (report-presentation), it is necessary to submit a report on the research work (3-5 pages) carried out on the selected task.

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Prerequisites

+

Machine learning methods.

+ + + +
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Lecturers

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+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Ivan Torshin +

+
+ + + + + + + + + + + + + +
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+ + +
+ + diff --git a/course/computational_geometry/index.html b/course/computational_geometry/index.html new file mode 100644 index 00000000..18f1c809 --- /dev/null +++ b/course/computational_geometry/index.html @@ -0,0 +1,366 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Computational Geometry Algorithms + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + +
+ +
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+ +
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+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Computational Geometry

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About

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The course discusses the basic algorithms of computational geometry.

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Syllabus

+ + +

Labworks

+

The course assumes the solution of several laboratory works.

+ +

Grading

+

The assessment is based on the results of laboratory work and an oral exam.

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Prerequisites

+

Machine learning, data structures and algorithms.

+ + + + +
+

Lecturers

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Leonid Mestetskiy +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + +
+ + diff --git a/course/deep_generative_models/index.html b/course/deep_generative_models/index.html new file mode 100644 index 00000000..716c7f73 --- /dev/null +++ b/course/deep_generative_models/index.html @@ -0,0 +1,457 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Deep Generative Models + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Deep Generative Models

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+ + + + + Course Website
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+ +

About

+

The course is devoted to modern generative models (mostly in the application to computer vision). Special attention is paid to the properties of various classes of generative models, their interrelationships, theoretical prerequisites and methods of quality assessment. The aim of the course is to introduce the student to widely used advanced methods of deep learning.

+ +

Syllabus

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    +
  1. Generative models overview and motivation. Problem statement. Divergence minimization framework. Autoregressive modelling.
    2. +
  2. Autoregressive models (WaveNet, PixelCNN). Bayesian Framework. Latent Variable Models (LVM). Variational lower bound (ELBO).
    3. +
  3. EM-algorithm, amortized inference. ELBO gradients, reparametrization trick. Variational Autoencoder (VAE).
    4. +
  4. VAE limitations. Posterior collapse and decoder weakening. Tighter ELBO (IWAE). Normalizing flows prerequisities.
    5. +
  5. Normalizing Flow (NF) intuition and definition.. Forward and reverse KL divergence for NF. Linear flows.
    6. +
  6. Autoregressive flows (gausian AR NF/inverse gaussian AR NF). Coupling layer (RealNVP). NF as VAE model.
    7. +
  7. Discrete data vs continuous model. Model discretization (PixelCNN++). Data dequantization: uniform and variational (Flow++). ELBO surgery and optimal VAE prior. Flow-based VAE prior.
    8. +
  8. Flows-based VAE posterior vs flow-based VAE prior. Likelihood-free learning. GAN optimality theorem.
    9. +
  9. Vanishing gradients and mode collapse, KL vs JS divergences. Adversarial Variational Bayes. Wasserstein distance. Wasserstein GAN (WGAN).
    10. +
  10. WGAN with gradient penality (WGAN-GP). Spectral Normalization GAN (SNGAN). f-divergence minimization. Evaluation of implicit models.
    11. +
  11. GAN evaluation (Inception score, FID, Precision-Recall, truncation trick). Discrete VAE latent representations.
    12. +
  12. Vector quantization, straight-through gradient estimation (VQ-VAE). Gumbel-softmax trick (DALL-E). Neural ODE. Adjoint method.
    13. +
  13. Continuous-in-time NF (FFJORD, Hutchinson’s trace estimator). Kolmogorov-Fokker-Planck equation and Langevin dynamic. SDE basics. Score matching (Sliced score matching, denoising score matching).
    14. +
  14. Noise conditioned score network (NCSN). Gaussian diffusion process. Denoising diffusion probabilistic model (DDPM).
    15. +
+ +

Labworks

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6 homeworks: theory and practice.

+ +

Grading

+

Each homework gives 13 points + an exam for 26 points. Final score: (number of points / 8) - 2.

+ +

Prerequisites

+

Statistics, machine learning, deep learning, intro to bayesian inference.

+ + + + +
+

Lecturers

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Roman Isachenko +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + Petr Mokrov +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + diff --git a/course/deep_learning/index.html b/course/deep_learning/index.html new file mode 100644 index 00000000..d61a2fa8 --- /dev/null +++ b/course/deep_learning/index.html @@ -0,0 +1,696 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Deep Learning + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+
+ + +
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+
+ +
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+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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+ + + + + + + + + + +
+ + + + + + +
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+ + + + + +
+

Deep Learning

+
+ + + + + +
+ +

About

+

An overview course on basic neural network models and their application to image, text, and sound processing tasks.

+ +

Syllabus

+ + +

Labworks

+

5 practical tasks and 1 lab work. Each task is evaluated from 10 points. The exam is evaluated from 10 points.

+ +

Grading

+

0.7 * semester points + 0.3 * exam points.

+ +

Prerequisites

+

Machine learning, statistics, optimization methods.

+ + + + +
+

Lecturers

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Dmitriy Kropotov +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Olga Grebenkova +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Andrey Filatov +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Anton Bishuk +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Konstantin Yakovlev +

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+ + +
+ + diff --git a/course/forecasting_methods/index.html b/course/forecasting_methods/index.html new file mode 100644 index 00000000..8b5eacc9 --- /dev/null +++ b/course/forecasting_methods/index.html @@ -0,0 +1,535 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Forecasting Methods + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+
+ + +
+ +
+
+ +
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+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
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Forecasting Methods

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+ + + + + +
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About

+

The course joins two parts of the problem statements in Machine Learning. The first part comes from the structure of the measured data. The data come from Physics, Chemistry and Biology and have intrinsic algebraic structure. This structure is part of the theory that stands behind the measurement. The second part comes from errors of the measurement. The stochastic nature errors request the statistical methods of analysis. So this course joins algebra and statistics. It is devoted to the problem of predictive model selection.

+ +

Syllabus

+ + +

Labworks

+

Two personal labworks on brain data analysis include the problem statement and the computational experiment. The delivery is a two-page report with the problem and experimental results, a code and a talk.

+ +

Grading

+

Questionnaires during lectures (3), two labworks (2+2), the final exam: topics and problems with discussion (3).

+ +

Prerequisites

+

Algebra, analysis and physics at the graduate level.

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Course page

+

with detailed schedule and materials

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Lecturers

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Vadim Strijov +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Alina Samokhina +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Denis Tikhonov +

+
+ + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/course/fundamental_ml_theorems/index.html b/course/fundamental_ml_theorems/index.html new file mode 100644 index 00000000..f2df501b --- /dev/null +++ b/course/fundamental_ml_theorems/index.html @@ -0,0 +1,375 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Fundamental Machine Learning Theorems + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Fundamental Machine Learning Theorems

+
+ + + + + +
+ +

About

+

The goal of the course is to learn how to rigorously formulate machine learning problems and to show the role of the mathematical approach. The skills acquired in this course are the basis for writing Bachelor’s, Master’s and Ph.D works in machine learning and applied mathematics. The course includes discussions of axiomatic systems, theorems and their proofs that are relevant in machine learning. Their influence on practical applications is discussed.

+ +

Syllabus

+ + +

Labworks

+

Presentation of the formulations, proofs and methods of application, significance, of theorems.

+ +

Grading

+

The quality of presentations and the quality of questions to the speaker from each student.

+ +

Prerequisites

+

Algebra and analysis of the third year of MIPT.

+ + + + +
+

Lecturers

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Vadim Strijov +

+
+ + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/course/image_processing_recognition/index.html b/course/image_processing_recognition/index.html new file mode 100644 index 00000000..ea45928d --- /dev/null +++ b/course/image_processing_recognition/index.html @@ -0,0 +1,373 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Image Processing and Recognition + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Image Processing and Recognition

+
+ + + + + +
+ +

About

+

The course is based on mathematical methods of pattern recognition used for the analysis and classification of images in computer vision systems. +Image transformations are considered in order to generate feature descriptions. The methods of point, spatial geometric, algebraic and inter-frame image processing are studied. Methods of feature generation based on the decomposition of images by basic functions, statistical analysis of image texture, as well as image shape analysis are considered. +Methods of construction of metrics for image comparison (comparison of spectral decompositions, overlay and alignment of images) are considered. And also questions of application of the studied methods in applied problems of computer vision. The tasks of text recognition in document images, the tasks of biometric identification of an individual by the texture of the iris, by the shape of the palm, fingerprint, face profile are considered.

+ +

Syllabus

+ + +

Labworks

+

Homeworks on image processing and classification.

+ +

Grading

+

The assessment is based on the results of laboratory work and an oral exam.

+ +

Prerequisites

+

Machine learning, linear algebra.

+ + + + +
+

Lecturers

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Leonid Mestetskiy +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/course/index.html b/course/index.html new file mode 100644 index 00000000..7ded250b --- /dev/null +++ b/course/index.html @@ -0,0 +1,557 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Course + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Bachelor

+
+
+ +
+ + + +
+

+ Automation of Scientific Research +

+
+ + + + + +
+

+ Bayesian Model Selection +

+
+ + + + + + + + + + + + + +
+

+ Deep Learning +

+
+ + + + + +
+

+ Forecasting Methods +

+
+ + + + + + + + + + + +
+

+ Introduction to Machine Learning +

+
+ + + + + + + +
+

+ Networks and Text Analysis +

+
+ + + + + + + +
+

+ Optimization methods in Machine Learning +

+
+ + + + + + + +
+

+ Recommender Systems +

+
+ + + + + + + + + +
+ +
+

Master

+
+
+ +
+ + + + + + + +
+

+ Bayesian Multimodeling +

+
+ + + + + +
+

+ Bioinformatics +

+
+ + + + + + + +
+

+ Deep Generative Models +

+
+ + + + + + + + + + + + + +
+

+ Intellectual Data Analysis +

+
+ + + + + + + +
+

+ Natural Language Processing +

+
+ + + + + + + + + + + +
+

+ Probabilistic Topic Models +

+
+ + + + + + + +
+

+ Creation of Intelligent Systems +

+
+ + + + + +
+

+ Signal Processing +

+
+ + + + + +
+

+ Software Engineering for Data Analysis +

+
+ + + +
+ +
+

No longer taught

+
+
+ +
+ + + + + + + + + + + +
+

+ Computational Geometry +

+
+ + + + + + + + + + + +
+

+ Fundamental Machine Learning Theorems +

+
+ + + + + +
+

+ Image Processing and Recognition +

+
+ + + + + + + + + + + + + +
+

+ Neural Architecture Search +

+
+ + + + + + + + + + + + + + + +
+ + + + +
+ + +
+ + diff --git a/course/intellectual_data_analysis/index.html b/course/intellectual_data_analysis/index.html new file mode 100644 index 00000000..39bd223e --- /dev/null +++ b/course/intellectual_data_analysis/index.html @@ -0,0 +1,432 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Intellectual Data Analysis + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Intellectual Data Analysis

+
+ + + + + +
+ +

About

+

The course introduces students to the full cycle of creating machine learning models for research purposes. +The main stages of the semester: analysis of an applied problem and formulation of the problem, building a model, performing a computational experiment, error analysis. +The result of the work of a group of students is a library of models for a fixed applied problem or class of problems.

+ +

Course page

+ +

Grading

+

Evaluated: the student’s qualifications and his personal contribution to the project.

+ + + + +
+

Lecturers

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Vadim Strijov +

+
+ + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Oleg Bakhteev +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/course/introduction_machine_learning/index.html b/course/introduction_machine_learning/index.html new file mode 100644 index 00000000..43603662 --- /dev/null +++ b/course/introduction_machine_learning/index.html @@ -0,0 +1,383 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Introduction to Machine Learning + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Introduction to Machine Learning

+
+ + + + + Course Website
+ + +
+ +

About

+

The course covers the main tasks of teaching by use cases: classification, clustering, regression, dimension reduction. The methods of their solution, both classical and new, created over the past 10-15 years, are being studied. The emphasis is on a deep understanding of the mathematical foundations, relationships, advantages and limitations of the methods under consideration. Theorems are mostly given without proofs.

+ +

Syllabus

+ + +

Labworks

+

No.

+ +

Grading

+

At the end of the course, students take an oral exam on all topics of the course.

+ +

Prerequisites

+

Probability theory, statistics, optimization methods, linear algebra.

+ + + + +
+

Lecturers

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Konstantin Vorontsov +

+
+ + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/course/natural_language_processing/index.html b/course/natural_language_processing/index.html new file mode 100644 index 00000000..5108e4ab --- /dev/null +++ b/course/natural_language_processing/index.html @@ -0,0 +1,445 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Natural Language Processing + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Natural Language Processing

+
+ + + + + +
+ +

About

+

The course covers the main tasks and mathematical methods of natural language processing.

+ +

Syllabus

+ + +

Labworks

+

The course includes four practical tasks and an exam. The deadline for completing each task is 2 weeks. You can get up to 10 points for each task. For each day of delay, a penalty of 1 point is assigned.

+ +

Grading

+

0.7 * hw points / 5 + 0.3 * exam points.

+ +

Prerequisites

+

Machine learning, deep learning, Python.

+ + + +
+

Lecturers

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Artem Popov +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/course/networks_text_analysis/index.html b/course/networks_text_analysis/index.html new file mode 100644 index 00000000..28b927e0 --- /dev/null +++ b/course/networks_text_analysis/index.html @@ -0,0 +1,373 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Networks and Text Analysis + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Networks and Text Analysis

+
+ + + + + +
+ +

About

+

The methods and technologies used in data mining and based on the concepts of similarity, proximity, analogy are considered. The idea of similarity is inherent in human thinking, it has given rise to a whole range of approaches for all fundamental tasks of IAD, among which the main focus of the course is on classification, regression recovery, clustering, recovery of missing data. +The theoretical basis for the construction, implementation and analysis of a wide range of models and methods of IAD is presented. Methods of constructing and calculating similarity functions, matching similarities on various sets of objects, synthesis of new ways of comparing objects based on existing ones are considered. A complex of technologies designed for efficient representation and processing of metric information by computing systems is considered. +Heuristic data models describing the initial information about recognition objects based on various implementations of the concept of similarity are investigated. The problems requiring solutions in the implementation of these models are considered. Special data structures and algorithms are being studied to effectively configure and use the studied models.

+ +

Syllabus

+ + +

Labworks

+

No.

+ +

Grading

+

Exam based on course materials.

+ +

Prerequisites

+

Machine learning, algorithms and data structures.

+ + + +
+

Lecturers

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Archil Meysuradze +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/course/neural_architecture_search/index.html b/course/neural_architecture_search/index.html new file mode 100644 index 00000000..08990f47 --- /dev/null +++ b/course/neural_architecture_search/index.html @@ -0,0 +1,372 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Neural Architecture Search + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+ +
+ + + + + +
+ +

About

+

The course is devoted to modern methods of constructing complex neural network architectures and choosing optimal structures.

+ +

Syllabus

+ + +

Самостоятельная работа

+

The laboratory work consists in the study of the architecture search method. The first job is to analyze a ready-made method, the second job is to propose and program your own method. The work report is a page of text with a formal description of the method with sufficient detail for code recovery and error analysis (basic criteria complexity, stability, accuracy). The interface to the class is fixed and common to everyone, as are the selections. There is a general table with the results, and a private error analysis of each method.

+ +

Оценивание

+

A total of 10 points, two points for answering questions during lectures, four points each for two laboratory work. It is not the accuracy of the approximation that is evaluated, but the quality of the code and error analysis.

+ +

Требуемые знания

+

Machine learning, deep learning, Bayesian model selection.

+ + + + +
+

Lecturers

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Mark Potanin +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/course/optimization_methods/index.html b/course/optimization_methods/index.html new file mode 100644 index 00000000..3990fe75 --- /dev/null +++ b/course/optimization_methods/index.html @@ -0,0 +1,354 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Optimization methods in Machine Learning + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Optimization methods in Machine Learning

+
+ + + + + +
+ +

About

+ +

Syllabus

+ +

Labworks

+ +

Grading

+ +

Prerequisites

+ + + + +
+

Lecturers

+
+ +
+ + + + + + + + + + +
+

+ + + + Aleksandr Beznosikov +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/course/probabilistic_topic_models/index.html b/course/probabilistic_topic_models/index.html new file mode 100644 index 00000000..a6f1c125 --- /dev/null +++ b/course/probabilistic_topic_models/index.html @@ -0,0 +1,371 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Probabilistic Topic Models + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Probabilistic Topic Models

+
+ + + + + +
+ +

About

+

The special course studies probabilistic topic modeling of collections of text documents. The topic model determines which topics are contained in a large text collection, and which topics each document belongs to. Topic models allow you to search for texts by meaning, not by keywords, and create a new generation of information search engines based on the paradigm of semantic exploratory search (exploratory search). Topic models for classification, categorization, segmentation, summarization of natural language texts, as well as for recommendation systems, analysis of bank transactional data, analysis of biomedical signals are considered. The special course develops a multi-criteria approach to the construction of models with specified properties - additive regularization of topic models (ARTM). It is based on the regularization of incorrectly set stochastic matrix decomposition problems. Particular attention is paid to the methods of linguistic regularization for modeling the coherence of the text. Students are supposed to conduct numerical experiments on model and real data using the BigARTM topic modeling library.

+ +

Syllabus

+ + +

Labworks

+

No.

+ +

Grading

+

The condition for passing the course is the performance of individual practical tasks.

+ +

Prerequisites

+

Linear algebra, mathematical analysis, probability theory.

+ + + +
+

Lecturers

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Konstantin Vorontsov +

+
+ + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/course/recommender_systems/index.html b/course/recommender_systems/index.html new file mode 100644 index 00000000..3bc06337 --- /dev/null +++ b/course/recommender_systems/index.html @@ -0,0 +1,457 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Recommender Systems + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Recommender Systems

+
+ + + + + Course Website
+ + +
+ +

About

+

Course objective is to provide comprehensive introduction to the field of Recommender Systems.

+ + + +

Syllabus

+
    +
  1. Introduction
    2. +
  2. Neighborhood-Based models
    3. +
  3. Matrix Factorization models
    4. +
  4. Content-based and Hybrid systems
    5. +
  5. Two-level models
    6. +
  6. Neural recommenders
    7. +
  7. Multi-armed bandits
    8. +
  8. Counterfactual evaluation
    9. +
+ +

Labworks

+

Two homeworks during the course

+ +

Grading

+

Based on homework results

+ +

Prerequisites

+

Machine learning, deep learning

+ + + + +
+

Lecturers

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Alexey Grishanov +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Anna Volodkevich +

+
+ + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/course/rnd_in_ai/index.html b/course/rnd_in_ai/index.html new file mode 100644 index 00000000..219428f4 --- /dev/null +++ b/course/rnd_in_ai/index.html @@ -0,0 +1,401 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Creation of Intelligent Systems + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Creation of Intelligent Systems

+
+ + + + + Course Website
+ + +
+ +

About

+

This is the extension of “Automation of Scientific Research” course. The work is organized in teams (2-3 people). Students will prepare weekly presentation of the team’s work: 5 minutes presentation + 5 minutes discussion with other students.

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Criteria for the project:

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  1. The entire project must be on GitHub under an OpenSource license (MIT)
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  2. The project must contain the code and instructions for launching it. +
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    1. The basic code in jupyter notebook to demonstrate the concept of work and plotting from the article should be run with colab.
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    2. The source code of the computational experiment should be run on a Unix system by executing two commands (possibly in a special docker image): +
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      • python3 train.py - for training models.
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      • python3 test.py - for testing, obtaining the results of the experiment.
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    3. The documentation for the code is sphinx.
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  3. The project should contain the manuscript of the article using a stylistic from arXiv - for unification.
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  4. If the project implies non-synthetic data, then there should be an instruction for obtaining this data, as well as a script for obtaining them. If the data is specific, then they need to be posted on one of the file storages.
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Syllabus

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Labworks

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Writing scientific paper.

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Grading

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There are 4 checkpoints in the course, 3 points are given for each

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  1. Research of the subject area - analysis of the problem.
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  2. Theoretical results.
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  3. Computational experiment.
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  4. Github project.
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Prerequisites

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Machine learning, deep learning, Python.

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Lecturers

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+ + + + Andrey Grabovoy +

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+ + diff --git a/course/signal_processing/index.html b/course/signal_processing/index.html new file mode 100644 index 00000000..f00b3ba8 --- /dev/null +++ b/course/signal_processing/index.html @@ -0,0 +1,368 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Signal Processing + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Intelligent Systems Phystech +
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+ + Machine Learning
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Signal Processing

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About

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The course is devoted to the use of methods of mathematical modelling and theoretical physics in signal processing. It applies methods for machine learning model selection to various types of signals: image, video and sound. It discusses techniques to construct systems of heterogenous signal models.

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Syllabus

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Labworks

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Two personal labworks on video signals include the problem statement and the computational experiment. The delivery is a two-page report with the problem and experimental results, a code and a talk.

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Grading

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Questionnaires during lectures (3), two labworks (2+2), the final exam: topics and problems with discussion (3).

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Prerequisites

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Algebra, analysis and physics at the postgraduate level.

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Lecturers

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+ + + + Vadim Strijov +

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+ + diff --git a/course/software_engineering_data_analysis/index.html b/course/software_engineering_data_analysis/index.html new file mode 100644 index 00000000..8876ceb2 --- /dev/null +++ b/course/software_engineering_data_analysis/index.html @@ -0,0 +1,372 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Software Engineering for Data Analysis + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Intelligent Systems Phystech +
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+ + Machine Learning
+ + Data Analysis
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Software Engineering for Data Analysis

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About

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The course covers the development of data processing systems and machine learning.

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As a result of mastering the course, students acquire the skills of industrial development of machine learning algorithms, conducting repeatable experiments, using big data, testing and project execution processes in the field of machine learning.

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Syllabus

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Labworks

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Practical tasks during the course + course project.

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Grading

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The final grade for the course is formed from the success of completing tasks during the semester - 10% for each task, and confirmation on an oral survey of ownership of each of the topics of the course (CODE, TEST, DATA, PROC) - 40% of the grade.

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Prerequisites

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Python.

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Lecturers

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+ + + + Anton Khritankov +

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+ + diff --git a/docker_test.sh b/docker_test.sh new file mode 100644 index 00000000..3ee93dbd --- /dev/null +++ b/docker_test.sh @@ -0,0 +1,3 @@ +# this is an extremely ineffective one-liner for testing our site +docker run --rm -it -v $(pwd):/data -p 4000:4000 -e LANG=C.UTF-8 -it ubuntu:20.04 /bin/bash -c "cd /data; apt-get update; apt-get install -y bundler; bundle install; bundle exec jekyll serve --host 0.0.0.0" + diff --git a/education/index.html b/education/index.html new file mode 100644 index 00000000..f2ac2852 --- /dev/null +++ b/education/index.html @@ -0,0 +1,582 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Educational program schedule + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Intelligent Systems Phystech +
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+ + Machine Learning
+ + Data Analysis
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Расписание

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Осенний семестр, 2024

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Занятия онлайн

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Расписание занятий

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4 курс, 7 семестр - вторник

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ВремяПредметПреподавателиФорма отчетностиЗачетные единицы
10:30-12:00Методы глубокого обучения: лекцияФилатов А.В., Яковлев К.Д.Дифф. зачет2
12:10-13:40Методы глубокого обучения: семинарФилатов А.В., Яковлев К.Д.  
14:30-16:00Байесовский выбор моделейАдуенко А.А., Яковлев К.Д.Дифф. зачет1
16:10-17:40Математические методы прогнозированияСамохина А.М., Тихонов Д.М.Дифф. зачет1
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5 курс, 9 семестр - вторник

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ВремяПредметПреподавателиФорма отчетностиЗачетные единицы
14:30-16:00Создание интеллектуальных системГрабовой А.В.Дифф. зачет2
16:10-17:40Байесовское мультимоделированиеБахтеев О.Ю.Дифф. зачет2
18:00-19:30Порождающие модели машинного обучения: лекцияИсаченко Р.В., Кондратенко В.Экзамен3
19:30-21:00Порождающие модели машинного обучения: семинарИсаченко Р.В., Кондратенко В.  
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6 курс, 11 семестр - четверг

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ВремяПредметПреподавателиФорма отчетностиЗачетные единицы
10:30-12:00Обработка сигналовСеверилов П.А.Экзамен3
12:10-13:40Интеллектуальный анализ данныхСтрижов В.В., Бахтеев О.Ю.Зачет2
14:30-16:00Вероятностные тематические моделиВоронцов К.В.Дифф. зачет2
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Ключевые даты

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Весенний семестр, 2025

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3 курс, 6 семестр – четверг

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ВремяПредметПреподавателиФорма отчетностиЗачетные единицы
12:10-13:40Введение в машинное обучениеГрабовой А.В., Воронцов К.В.Дифф. зачет1
14:30-16:00Практикум по программированию на языке ПитонАпишев М.А.Зачет1
16:10-17:40Создание интеллектуальных системГрабовой А.В.Зачет1
17:50-19:20Автоматизация научных исследований (Моя первая научная статья)Грабовой А.В., Бахтеев О.Ю.Дифф. зачет1
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4 курс, 8 семестр – вторник

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ВремяПредметПреподавателиФорма отчетностиЗачетные единицы
10:30-12:00Рекомендательные системыГришанов А.В., Володкевич А.А.Дифф. зачет2
12:50-14:20Методы оптимизации в машинном обученииБезносиков А.Н.Дифф. зачет1
14:30-16:00Байесовский выбор моделейАдуенко А.А.Экзамен2
16:10-17:40Математические методы прогнозированияСамохина А.М.Дифф. зачет3
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5 курс, 10 семестр – вторник

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ВремяПредметПреподавателиФорма отчетностиЗачетные единицы
10:30-12:00БиоинформатикаТоршин И.Ю.Дифф. зачет1
12:50-14:20Методы оптимизации в машинном обученииБезносиков А.Н.Дифф. зачет2
14:30-16:00Байесовское мультимоделированиеБахтеев О.Ю.Экзамен2
16:10-17:40Планирование проектов по созданию программного обеспеченияХританков А.С.Дифф. зачет1
17:50-19:20Создание интеллектуальных системГрабовой А.А.Экзамен2
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Ключевые даты

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Документы и ссылки

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+ Intelligent Systems Phystech +
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+ + Machine Learning
+ + Data Analysis
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Class timetable

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Department of Intelligent Systems graduates bachelors and masters in the field of study “Applied Mathematics and physics”.

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Announcements and Information

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Online channels:

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+ + diff --git a/javascript/transition.js b/javascript/transition.js new file mode 100644 index 00000000..11a1e588 --- /dev/null +++ b/javascript/transition.js @@ -0,0 +1,59 @@ +/* ======================================================================== + * Bootstrap: transition.js v3.3.6 + * http://getbootstrap.com/javascript/#transitions + * ======================================================================== + * Copyright 2011-2016 Twitter, Inc. + * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE) + * ======================================================================== */ + + ++function ($) { + 'use strict'; + + // CSS TRANSITION SUPPORT (Shoutout: http://www.modernizr.com/) + // ============================================================ + + function transitionEnd() { + var el = document.createElement('bootstrap') + + var transEndEventNames = { + WebkitTransition : 'webkitTransitionEnd', + MozTransition : 'transitionend', + OTransition : 'oTransitionEnd otransitionend', + transition : 'transitionend' + } + + for (var name in transEndEventNames) { + if (el.style[name] !== undefined) { + return { end: transEndEventNames[name] } + } + } + + return false // explicit for ie8 ( ._.) + } + + // http://blog.alexmaccaw.com/css-transitions + $.fn.emulateTransitionEnd = function (duration) { + var called = false + var $el = this + $(this).one('bsTransitionEnd', function () { called = true }) + var callback = function () { if (!called) $($el).trigger($.support.transition.end) } + setTimeout(callback, duration) + return this + } + + $(function () { + $.support.transition = transitionEnd() + + if (!$.support.transition) return + + $.event.special.bsTransitionEnd = { + bindType: $.support.transition.end, + delegateType: $.support.transition.end, + handle: function (e) { + if ($(e.target).is(this)) return e.handleObj.handler.apply(this, arguments) + } + } + }) + +}(jQuery); \ No newline at end of file diff --git a/materials/conferences/index.html b/materials/conferences/index.html new file mode 100644 index 00000000..aa440988 --- /dev/null +++ b/materials/conferences/index.html @@ -0,0 +1,4593 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Conferences on scientific topics of the department + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Conferences & Journals on scientific topics of the department

+ +

The conferences mainly are retrieved from here http://www.guide2research.com/topconf/ (+ CORE2021: https://www.core.edu.au/conference-portal + some Russian and conferences well known by me).

+ +

The journals are retrieved from here https://www.scimagojr.com/journalrank.php.

+ +

References:

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    +
  1. https://tinyurl.com/bahleg-conf
    2. +
  2. https://tinyurl.com/bahleg-journals
    3. +
+ +

Conferences

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Conference nameCategoryConference programURLRankRank system
SIGBOVIKSpecific http://sigbovik.org/--
ECIR : European Conference on Information RetrievalIR/MiningDemo, Industrial, Tutorials, Workshopshttps://www.ecir2024.org/ACORE2021
SIGIR: International ACM SIGIR Conference on Research and Development in Information RetrievalIR/Mining https://sigir-2024.github.io/ACORE2021
WWW: International World Wide Web ConferencesIR/MiningDemo, StudentThesis / Doctor symposium, Tutorials, Workshopshttps://www2024.thewebconf.org/ACORE2021
ESWC : Extended Semantic Web ConferenceIR/Mining https://2024.eswc-conferences.org/ACORE2021
MSR : Mining Software RepositoriesIR/Mining, Specific https://2024.msrconf.org/ACORE2021
WSDM : ACM International Conference on Web Search and Data MiningIR/Mining https://www.wsdm-conference.org/2024/ACORE2021
PODS : ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database SystemsIR/MiningDemo, Industrial, Tutorials, Workshopshttps://2024.sigmod.org/ACORE2021
RecSys : ACM Conference on Recommender SystemsIR/MiningTutorials, Workshopshttps://recsys.acm.org/recsys24/ACORE2021
EDBT : International Conference on Extending Database TechnologyIR/MiningStudentThesis / Doctor symposium, Workshopshttps://edbt.org/ACORE2021
DASFAA : International Conference on Database Systems for Advanced ApplicationsIR/Mining https://www.dasfaa2024.org/BCORE2021
SSBSE : International Conference on Search based Software EngineeringIR/Mining https://ssbse.info/BCORE2021
UMAP : International Conference on User Modelling, Adaptation, and PersonalizationIR/Mining, Specific https://www.um.org/umap2024/BCORE2021
Pacific Asia Conference on Language, Information and ComputationIR/Mining  BCORE2021
International Conference on Formal Ontology in Information SystemsIR/Mining, Specific  BCORE2021
ADBIS : Advances in Databases and Information SystemsIR/MiningStudentThesis / Doctor symposium, Tutorials, Workshopshttps://conferences.sigappfr.org/adbis2024/BCORE2021
WISE : International Conference on Web Information Systems EngineeringIR/Mining https://wise2024-qatar.com/BCORE2021
Workshop on Logic, Language, Information and ComputationIR/Mining, NLP https://wollic2024.inf.unibe.ch/BCORE2021
EKAW : Knowledge Engineering and Knowledge ManagementIR/Mining  BCORE2021
TPDL : International Conference on Theory and Practice of Digital LibrariesIR/Mining  BCORE2021
International Conference on Knowledge-Based and Intelligent Information and Engineering SystemsIR/MiningWorkshopshttp://kes2024.kesinternational.org/BCORE2021
Asian Conference on Intelligent Information and Database SystemsIR/Mining https://aciids.pwr.edu.pl/2024/BCORE2021
ADMA : International Conference on Advanced Data Mining and ApplicationsIR/Mining https://adma2024.github.io/BCORE2021
WI : IEEE/WIC/ACM International Conference on Web IntelligenceIR/MiningSpecialSession, Workshops BCORE2021
International Symposium on Computer and Information SciencesIR/Mining https://www.iscsic.org/CCORE2021
European-Japanese Conference on Information Modelling and Knowledge BasesIR/Mining https://ejc2024.ds.musashino-u.ac.jp/CCORE2021
International Conference on Information Technology and ApplicationsIR/MiningSpecialSession, Workshopshttps://www.icita.world/#/CCORE2021
International Conference on Legal Knowledge and Information SystemsIR/Mining, Specific  CCORE2021
Asia Information Retrieval SymposiumIR/Mining  CCORE2021
TRECIR/Mining, NLP  --
ASONAM : International Conference on Advances in Social Network Analysis and MiningIR/Mining  --
IEEE International Conference on Information and AutomationIR/Mining, ML/CS, Specific  --
WebSci : ACM on Web Science ConferenceIR/MiningTutorials, Workshopshttps://websci24.org/--
ISWC : International Semantic Web ConferenceIR/MiningTutorials, Workshops --
BTAS : IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS)IR/Mining, Specific  --
RussirIR/Mining, NLP  --
Statistical and Scientific Database ManagementIR/Mining https://ssdbm.org/2024/--
International Conference on Information and Knowledge EngineeringIR/Mining, Specific  --
International Conference on the Theory of Information RetrievalIR/Mining  --
IJCB : International Joint Conference on BiometricsIR/Mining, SpecificDemo, StudentThesis / Doctor symposium, Tutorials --
CHIIR : Conference on Human Information Interaction and RetrievalIR/Mining https://chiir2024.github.io/--
Conference on Information Sciences and SystemsIR/Mining https://ee-ciss.princeton.edu/--
International Baltic Conference on Databases and Information SystemsIR/Mining  --
ICWSM : International Conference on Web and Social MediaIR/Mining https://www.icwsm.org/2024/index.html/--
BigMM : IEEE International Conference on Multimedia Big DataIR/Mining  --
SemEval : International Workshop on Semantic EvaluationCV, IR/Mining, NLP, Signal https://semeval.github.io/SemEval2024/--
AVSS : IEEE International Conference on Advanced Video and Signal-Based SurveillanceSignal https://zinc.cse.buffalo.edu/ubmdfl/AVSS2024/index.phpBCORE2021
MMSP : IEEE Workshop on Multimedia Signal ProcessingSignalDemo, SpecialSession BCORE2021
International Conference on Image and Signal ProcessingSignal https://csita2024.org/ispr/indexCCORE2021
IEEE Symposium on Computational intelligence for Multimedia Signal and Vision ProcessingSignal  CCORE2021
DCASE : Detection and Classification of Acoustic Scenes and EventsSignalContests, Workshops --
ISMIR : International Society for Music Information Retrieval ConferenceIR/Mining, Signal, SpecificTutorialshttps://ismir2024.ismir.net/--
EUSIPCO : European Signal Processing ConferenceSignalTutorials, Workshopshttps://eusipcolyon.sciencesconf.org/--
International Conference on Robotics, Vision, Signal Processing and Power Applications (was ROVPIA)Signal, Specific  --
ICASSP: International Conference on Acoustics, Speech and Signal ProcessingSignal https://2024.ieeeicassp.org/--
SLT : IEEE Spoken Language Technology WorkshopSignalContests, Demo, Hackaton, Workshops --
ACM Symposium on Eye Tracking Research and ApplicationsCV, Signal, Specific https://etra.acm.org/2024/--
International Conference on Advanced Technologies For Signal & Image ProcessingSignal  --
WASPAA : IEEE Workshop on Applications of Signal Processing to Audio and AcousticsSignal  --
SPAWCSignal https://spawc2024.org/--
APSIPA : Asia-Pacific Signal and Information Processing Association Annual Summit and ConferenceSignal  --
SSP : IEEE Statistical Signal Processing WorkshopSignal  --
INTERSPEECH: Conference of the International Speech Communication AssociationSignal https://interspeech2024.org/--
MIPR : IEEE Conference on Multimedia Information Processing and RetrievalIR/Mining, SignalTutorials, Workshops --
ACSSC : Asilomar Conference on Signals, Systems and ComputersML/CS, Signal  --
WCSP : International Conference on Wireless Communications and Signal ProcessingSignal  --
SAM : IEEE Sensor Array and Multichannel Signal Processing WorkshopSignal https://2024.ieeesam.org/--
ICME: International Conference on Multimedia and ExpoCV, NLP, Signal https://2024.ieeeicme.org/ACORE2021
EACL : Conference of the European Chapter of the Association for Computational LinguisticsNLP https://2024.eacl.org/ACORE2021
CoNLL: Conference on Computational Natural Language LearningNLP  ACORE2021
ACL: Annual Meeting of the Association for Computational LinguisticsNLP https://2024.aclweb.org/ACORE2021
EMNLP: Conference on Empirical Methods in Natural Language ProcessingNLPTBA ACORE2021
COLING: International Conference on Computational LinguisticsNLPTutorials, Workshopshttps://lrec-coling-2024.org/ACORE2021
NAACL: North American Chapter of the Association for Computational LinguisticsNLPDemo, Industrial, Workshopshttps://2024.naacl.org/ACORE2021
SIGDIAL : Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)NLPSpecialSessionhttps://2024.sigdial.org/BCORE2021
IJCNLP : International Joint Conference on Natural Language Processing (IJCNLP)NLPTutorials, Workshops B-
DAS : IAPR International Workshop on Document Analysis SystemsNLPSpecialSession BCORE2021
NLDB : International Conference on Applications of Natural Language to Information SystemsNLP https://nldb2024.di.unito.it/CCORE2021
LREC : International Conference on Language Resources and Evaluation (LREC)NLP, Signal https://lrec-coling-2024.org/CCORE2021
DialogueNLPContestshttp://www.dialog-21.ru/--
CLEF : International Conference of the Cross-Language Evaluation Forum for European LanguagesCV, IR/Mining, NLP, Signal https://clef2024.clef-initiative.eu/--
SEM : Joint Conference on Lexical and Computational SemanticsNLP https://sites.google.com/view/starsem2024--
International Conference on Recent Advances in Natural Language ProcessingNLPTutorials, Workshops --
AINLNLP  --
IROS: International Conference on Intelligent Robots and SystemsCVTutorials, Workshops ACORE2021
ACMMM: ACM MultimediaCV, NLP, SignalDemo, StudentThesis / Doctor symposium, Workshops ACORE2021
ICCV: International Conference on Computer VisionCVTBA ACORE2021
ECCV: European Conference on Computer VisionCV https://eccv2024.ecva.net/ACORE2021
MICCAI : Medical Image Computing and Computer Assisted InterventionCV, Specific http://www.miccai.org/ACORE2021
ICDAR : International Conference on Document Analysis and RecognitionCV, IR/Mining, NLP https://icdar2024.net/ACORE2021
WACV: Winter Conference on Applications of Computer VisionCV https://wacv2024.thecvf.com/ACORE2021
CVPR: IEEE Conference on Computer Vision and Pattern RecognitionCVTutorials, Workshopshttps://cvpr.thecvf.com/ACORE2021
ICMR: ACM International Conference on Multimedia RetrievalCV, IR/Mining, NLP, Signal http://icmr2024.org/BCORE2021
Advanced Concepts for Intelligent Vision SystemsCV  BCORE2021
ICIP: International Conference on Image ProcessingCVDemo, SpecialSession, Tutorials, Workshopshttps://2024.ieeeicip.org/BCORE2021
Image and Vision Computing ConferenceCV  BCORE2021
ACCV: Asian Conference on Computer VisionCVDemo, StudentThesis / Doctor symposium, Tutorials, Workshopshttps://accv2024.org/BCORE2021
FG : IEEE International Conference on Automatic Face & Gesture RecognitionCV https://fg2024.ieee-biometrics.org/CCORE2021
International Conference on Control, Automation, Robotics and VisionCV, Specific  CCORE2021
International Conference on Computer Vision SystemsCVTutorials, Workshops CCORE2021
International Conference on Machine VisionCVSpecialSession CCORE2021
BMVC: British Machine Vision ConferenceCVWorkshops --
MLMI : International Workshop on Machine Learning in Medical ImagingCV  --
3DV : International Conference on 3D VisionCVDemo, Tutorialshttps://3dvconf.github.io/2024/--
ISBI : IEEE International Symposium on Biomedical ImagingCV, SpecificSpecialSession, Tutorialshttps://biomedicalimaging.org/2024/--
International Conference on Computer Vision and GraphicsCV  --
International Machine Vision and Image Processing ConferenceCVWorkshops --
Machine Vision ApplicationsCV  --
International Conferences in Central Europe on Computer Graphics, Visualization and Computer VisionCV  --
NeurIPS: Neural Information Processing SystemsML/CSBestPaperAward, Demo, Industrial, StudentPaper, Tutorials, Workshopshttps://nips.cc/Conferences/2023ACORE2021
IJCAI: International Joint Conference on Artificial IntelligenceML/CS https://ijcai24.org/ACORE2021
ECMLPKDD: European Conference on Machine learning and knowledge discovery in databasesIR/Mining, ML/CSTutorials, Workshopshttps://2024.ecmlpkdd.org/ACORE2021
ICML: International Conference on Machine LearningML/CS https://icml.cc/Conferences/2024ACORE2021
PAKDD: Pacific-Asia Conference on Knowledge Discovery and Data MiningIR/Mining, ML/CSTBAhttps://pakdd2024.org/ACORE2021
SIGKDD : ACM SIGKDD International Conference on Knowledge discovery and data miningIR/Mining, ML/CS https://kdd.org/kdd2024/ACORE2021
LAK : International Conference on Learning Analytics And KnowledgeIR/Mining, ML/CSStudentThesis / Doctor symposiumhttps://www.solaresearch.org/events/lak/lak24/ACORE2021
ICLR: International Conference on Learning RepresentationsML/CSTBAhttps://iclr.cc/Conferences/2024ACORE2021
ICDE : International Conference on Data Engineering WorkshopsML/CS https://icde2024.github.io/ACORE2021
CIKM: ACM International Conference on Information and Knowledge ManagementIR/Mining, ML/CS https://www.cikm2024.org/ACORE2021
European Conference on Artificial IntelligenceML/CSTutorials, Workshopshttps://www.ecai2024.eu/ACORE2021
IEEE International Conference on Data Science and Advanced AnalyticsML/CSTutorialshttps://conferences.sigappfr.org/dsaa2023/ACORE2021
AISTATS: International Conference on Artificial Intelligence and StatisticsML/CS https://aistats.org/aistats2024/ACORE2021
LICS : IEEE Symposium on Logic in Computer ScienceML/CS, Specific https://lics.siglog.org/lics24/ACORE2021
CIDR : Conference on Innovative Data Systems ResearchML/CS http://www.cidrdb.org/cidr2024/index.htmlACORE2021
SDM : SIAM International Conference on Data Mining (SDM)ML/CS https://www.siam.org/conferences/cm/conference/sdm24ACORE2021
KR: International Conference on Principles of Knowledge Representation and ReasoningIR/Mining, ML/CSStudentThesis / Doctor symposium, Tutorials, Workshopshttps://kr.org/KR2024/ACORE2021
SODA : ACM SIAM Symposium on Discrete AlgorithmsML/CS https://www.siam.org/conferences/cm/conference/soda24ACORE2021
ICDMW : IEEE International Conference on Data MiningML/CSTutorials, Workshopshttps://www.cloud-conf.net/icdm2023/ACORE2021
UAI: Conference on Uncertainty in Artificial IntelligenceML/CS https://www.auai.org/uai2024/ACORE2021
Logics in Artificial Intelligence, European ConferenceML/CS, Specific  ACORE2021
COLT: Conference on Learning TheoryML/CS https://learningtheory.org/colt2024/ACORE2021
SIGMOD : ACM SIGMOD International Conference on Management of DataML/CSTBAhttps://2024.sigmod.org/ACORE2021
STOC : ACM Symposium on Theory of ComputingML/CS, Specific http://acm-stoc.org/stoc2024/ACORE2021
AAAI: Association for the Advancement of Artificial IntelligenceML/CS https://aaai.org/aaai-conference/ACORE2021
International Conference on Artificial Intelligence in EducationML/CS, Specific https://www.aied2023.org/ACORE2021
ICPR : International Conference on Pattern RecognitionML/CS http://www.icprs.org/BCORE2021
FUZZ : IEEE International Conference on Fuzzy SystemsML/CS  BCORE2021
International Conference on Tools with Artificial IntelligenceML/CS  BCORE2021
Australasian Joint Conference on Artificial IntelligenceML/CSTutorials, Workshops BCORE2021
Educational Data MiningIR/Mining, ML/CS, Specific https://educationaldatamining.org/edm2024/BCORE2021
International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming for Combinatorial Optimization ProblemsML/CS https://sites.google.com/view/cpaior2024BCORE2021
Big Data : IEEE International Conference on Big DataIR/Mining, ML/CSSpecialSession, Tutorials, Workshopshttps://bigdataieee.org/BigData2024/BCORE2021
DCC : Data Compression ConferenceML/CS, Specific https://www.cs.brandeis.edu/~dcc/index.htmlBCORE2021
International Conference on Scientific and Statistical Data Base ManagementML/CS https://ssdbm.org/2024/BCORE2021
Web and Big DataIR/Mining, ML/CSWorkshops BCORE2021
Pacific Rim International Conference on Artificial IntelligenceML/CSTutorials, Workshops BCORE2021
IFIP WG 11.3 Working Conference on Data and Applications Security (also known as DBSEC)ML/CS, Specific  BCORE2021
Australian Data Mining ConferenceIR/Mining, ML/CSStudentThesis / Doctor symposium, Tutorials, Workshops BCORE2021
SAC : ACM Symposium on Applied ComputingML/CS http://www.sigapp.org/sac/sac2024/BCORE2021
International Conference on Agents and Artificial IntelligenceML/CSDemo, Panel, SpecialSession, StudentThesis / Doctor symposium, Tutorials, Workshopshttps://icaart.scitevents.org/BCORE2021
Artificial Intelligence in Medicine in EuropeML/CS, Specific https://www.aimedicine.info/aime24/BCORE2021
European Symposium on Artificial Neural NetworksML/CS https://www.esann.org/BCORE2021
SMC : IEEE International Conference on Systems, Man and CyberneticsML/CSTutorials, Workshopshttps://ieeesmc2024.org/BCORE2021
International Conference on Modelling Decisions for Artificial IntelligenceML/CS http://www.mdai.cat/mdai2024/BCORE2021
International Conference on Neural Information ProcessingML/CSTutorials, Workshops BCORE2021
Intelligent Data AnalysisML/CS https://ida2024.org/BCORE2021
IV : IEEE Intelligent Vehicles SymposiumML/CS, Specific https://2024.ieee-iv.org/BCORE2021
IJCNN: International Joint Conference on Neural NetworksML/CS  BCORE2021
Data Warehousing and Knowledge DiscoveryIR/Mining, ML/CSWorkshopshttps://www.dexa.org/dawak2024BCORE2021
CEC : IEEE Congress on Evolutionary ComputationML/CS, Specific  BCORE2021
ISIT : IEEE International Symposium on Information TheoryML/CS https://2024.ieee-isit.org/homeBCORE2021
International Conference on Intelligent Data Engineering and Automated LearningML/CS, SpecificSpecialSessionhttps://ideal2023.uevora.pt/CCORE2021
EUROML/CS https://euro2024cph.dk/CCORE2021
Artificial Intelligence Applications and InnovationsML/CS https://ifipaiai.org/CCORE2021
International Symposium on Artificial Life and RoboticsML/CS https://isarob.org/symposium/CCORE2021
International FLINS Conference on Robotics and Artificial Intelligence (was International Fuzzy Logic and Intelligent technologies in Nuclear Science Conference)ML/CS  CCORE2021
International Conference on Engineering Applications of Neural NetworksML/CS https://eannconf.org/2024/CCORE2021
IEEE/ACM International Conference on Big Data Computing, Applications and TechnologiesML/CSWorkshopshttps://bdcat-conference.org/CCORE2021
IEEE Symposium on Computational Intelligence and Data MiningML/CSWorkshops CCORE2021
International Conference on Internet of Things, Big Data and SecurityML/CSDemo, Panel, SpecialSession, Tutorials, Workshopshttps://iotbds.scitevents.org/CCORE2021
International Symposium on Neural NetworksML/CS https://conference.cs.cityu.edu.hk/isnn/CCORE2021
FUSION : International Conference on Information FusionML/CS  CCORE2021
International Conference on Machine Learning and ApplicationsML/CSSpecialSessionhttps://www.icmla-conference.org/icmla24/CCORE2021
International Cross-Domain Conference for Machine Learning and Knowledge ExtractionIR/Mining, ML/CS, NLPSpecialSession CCORE2021
ICANN: International Conference on Artificial Neural NetworksML/CS https://e-nns.org/icann2024/CCORE2021
International Conference on Artificial Intelligence and LawML/CS, Specific  CCORE2021
International Conference on Data Science, Technology and ApplicationsML/CSTBAhttps://data.scitevents.org/CCORE2021
International Conference on the Statistical Analysis of Textual DataML/CS, NLP  CCORE2021
International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed ComputingML/CSSpecialSession, Workshopshttps://acisinternational.org/conferences/snpd-2024/CCORE2021
International Conference on Model and Data EngineeringML/CSWorkshops CCORE2021
IEEE International Symposium on Artificial LifeML/CS, Specific  CCORE2021
International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert SystemsML/CS  CCORE2021
FRUCTML/CSPostershttps://www.fruct.org/conferences/35/call-for-participation/--
MMPR/IOIML/CS  --
AISTCV, IR/Mining, ML/CS, NLP https://aistconf.org/--
L@S : ACM Conference on Learning @ ScaleML/CS https://learningatscale.hosting.acm.org/las2024/--
International Work-Conference on Artificial and Natural Neural NetworksML/CS  --
International Symposium on Artificial Intelligence and MathematicsML/CS https://isaim2024.cs.ou.edu/--
MIPT conferenceML/CS https://conf.mipt.ru/--
SGAI International Conference on Artificial IntelligenceML/CS  --
International Conference on Hybrid Artificial Intelligence SystemsML/CS  --
International Conference on Artificial Intelligence: Methodology, Systems, ApplicationsML/CS  --
IEEE International Conference on Data Science and EngineeringML/CS  --
Portuguese Conference on Artificial IntelligenceML/CSStudentThesis / Doctor symposium --
LomonosovML/CS https://lomonosov-msu.ru/eng/event/9000/--
International Conference on Machine Learning and CyberneticsML/CS https://www.icmlc.com/--
Conference on Visualization and Data AnalysisCV, ML/CS  --
AutoMLML/CSTutorials, Workshopshttps://2024.automl.cc/--
International Conference on Distributed Computing and Artificial IntelligenceML/CS  --
Florida Artificial Intelligence Research Society ConferenceML/CS https://www.flairs-37.info/--
International Work-conference on the Interplay between Natural and Artificial ComputationML/CS  --
International Conference on Artificial IntelligenceML/CS  --
GECCO: Genetic and Evolutionary Computation ConferenceML/CS, Specific https://gecco-2024.sigevo.org/HomePage--
Language, Data and KnowledgeIR/Mining, ML/CS, NLPPosters, Tutorials, Workshops --
Asian Conference on Machine LearningML/CSWorkshops --
AIES : AAAI/ACM Conference on AI, Ethics, and SocietyML/CS, Specific  --
International Conference on Artificial Intelligence and Soft ComputingML/CS https://icaisc.eu/--
+ +

Journals

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Journal nameCategoryImpactURL
Foundations and Trends in Machine LearningML38.78https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=34
International Journal of Information ManagementML21.35https://robotics.sciencemag.org/
Science RoboticsML, Specific17.02https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=9670
IEEE Transactions on Pattern Analysis and Machine IntelligenceCV, Comp. Math, ML15.84https://www.journals.elsevier.com/signal-processing
Nature Machine IntelligenceML13.63https://www.frontiersin.org/journals/robotics-and-ai
Artificial Intelligence ReviewML, NLP11.67https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6570654
IEEE Transactions on Neural Networks and Learning SystemsML10.47https://www.osapublishing.org/josaa/home.cfm
IEEE Transactions on Fuzzy SystemsComp. Math, ML10.12https://www.springer.com/journal/521
ACM Transactions on Intelligent Systems and TechnologyML9.9https://www.springer.com/journal/11721
Neural NetworksML9.7https://www.journals.elsevier.com/neurocomputing
Expert Systems with ApplicationsML9.6https://www.springer.com/journal/12559
International Journal of Intelligent SystemsML9.34https://www.comsoc.org/publications/journals/ieee-tccn
Soft RoboticsML, Specific9.22http://www.jmlr.org/
Journal of Intelligent ManufacturingML9.18https://www.journals.elsevier.com/international-journal-of-information-management/
CAAI Transactions on Intelligence TechnologyML9.11???
Knowledge-Based SystemsML8.66https://www.sciencedirect.com/journal/pattern-recognition
Engineering Applications of Artificial IntelligenceML8.64https://www.journals.elsevier.com/digital-signal-processing
Pattern RecognitionCV, ML, NLP, Signal8.54https://www.springer.com/journal/11548
Advanced Engineering InformaticsML8.53https://link.springer.com/journal/10845
Information SciencesML8.51https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6221037
Artificial Intelligence in MedicineML, Specific8.3https://www.journals.elsevier.com/neural-networks
IEEE/CAA Journal of Automatica SinicaML7.7https://onlinelibrary.wiley.com/journal/14680394
International Journal of Robotics ResearchML, Specific7.38https://onlinelibrary.wiley.com/journal/1098111x
IEEE Transactions on Cognitive Communications and NetworkingML7.12https://www.journals.elsevier.com/fuzzy-sets-and-systems
NeurocomputingML6.19https://www.springer.com/journal/10115
Fuzzy Optimization and Decision MakingML6.06http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=91
Cognitive Systems ResearchML5.99https://www.springer.com/journal/10951
Minds and MachinesML5.92https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7274989
IEEE Intelligent SystemsML5.82http://www.elsevier.com/wps/find/journaldescription.cws_home/505651/description#description
IEEE Computational Intelligence MagazineML5.71https://www.mdpi.com/journal/jimaging
Pattern Recognition LettersCV, ML, NLP, Signal5.67https://www.springer.com/journal/10700
Computational LinguisticsML, NLP5.63http://journals.cambridge.org/action/displayJournal?jid=NLE
Neural Computing and ApplicationsML5.6https://www.journals.elsevier.com/journal-of-memory-and-language
Artificial IntelligenceML, NLP5.57https://www.sciencedirect.com/journal/medical-image-analysis
Applied IntelligenceML5.44https://www.journals.elsevier.com/knowledge-based-systems
Integrated Computer-Aided EngineeringComp. Math, ML5.44http://online.liebertpub.com/soro
Journal of Machine Learning ResearchML5.41https://journals.sagepub.com/home/ijr
Journal of Parallel and Distributed ComputingML, Specific5.27https://www.tandfonline.com/toc/teta20/current
Progress in Artificial IntelligenceML5.2https://www.springer.com/journal/10339
Artificial Intelligence and LawML, Specific4.94https://www.springer.com/journal/10851
Fuzzy Sets and SystemsML4.76https://www.journals.elsevier.com/artificial-intelligence/
ACM Transactions on Human-Robot InteractionML4.69???
International Journal of Machine Learning and CyberneticsCV, ML4.66https://www.iospress.nl/journal/integrated-computer-aided-engineering/
Journal of Artificial Intelligence and Soft Computing ResearchCV, ML4.62https://www.tandfonline.com/toc/hscc20/current
IEEE Transactions on Human-Machine SystemsML, Signal4.6https://www.journals.elsevier.com/engineering-applications-of-artificial-intelligence
Machine LearningML4.54https://dl.acm.org/journal/tcps
Design StudiesML, Specific4.36https://www.springer.com/journal/41315
International Journal of Approximate ReasoningML, Specific4.31https://www.hindawi.com/journals/acisc/
International Journal of Fuzzy SystemsComp. Math, ML4.23https://www.journals.elsevier.com/advanced-engineering-informatics
Frontiers in NeuroroboticsML, Specific4.08http://www.springer.com/computer+science/ai/journal/10489
Applied Computational Intelligence and Soft ComputingML4.07https://journals.sagepub.com/home/arx
Network NeuroscienceML4.07https://www.springer.com/journal/11067
Autonomous RobotsML, Specific3.94https://www.springer.com/journal/10032
Big Data and Cognitive ComputingML3.9https://www.springer.com/journal/498
Journal of Intelligent and Robotic Systems: Theory and ApplicationsML, Specific3.61https://www.springer.com/journal/10601
Journal of Artificial Intelligence ResearchML3.59https://www.journals.elsevier.com/expert-systems-with-applications
Frontiers in Robotics and AIML3.47???
IEEE Transactions on Cognitive and Developmental SystemsML3.45https://onlinelibrary.wiley.com/journal/17568765
RoboticsML, Specific3.4https://dl.acm.org/journal/jacm
Autonomous Agents and Multi-Agent SystemsML3.38???
Swarm IntelligenceML, Specific3.31https://www.journals.elsevier.com/information-sciences
Intelligent Service RoboticsML, Specific3.15https://www.mitpressjournals.org/netn
Digital Signal Processing: A Review JournalComp. Math, ML, Signal3.15http://jaiscr.eu/
Expert SystemsComp. Math, ML3.09https://www.jair.org/index.php/jair
ACM Transactions on Cyber-Physical SystemsML3.08http://www.springer.com/computer+science/ai/journal/11063
Knowledge and Information SystemsML3.06https://link.springer.com/journal/11263
Computational IntelligenceComp. Math, ML3.02https://www.springer.com/journal/10458
Evolutionary IntelligenceML2.96https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5962385
Journal of Intelligent Information SystemsML2.94https://www.mitpressjournals.org/loi/coli
Applied Artificial IntelligenceML2.92http://www.computability.de/journal/
AI and SocietyML2.87https://www.iospress.nl/journal/argument-computation/
Journal of the ACMML2.87https://www.journals.elsevier.com/design-studies
AI MagazineML2.87https://www.springer.com/journal/10844
Journal of Experimental and Theoretical Artificial IntelligenceML2.85https://www.springer.com/journal/10732
Systems Science and Control EngineeringML2.8http://www.actapress.com/Content_of_Journal.aspx?JournalID=119
Neural Processing LettersML2.8https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4200690
Topics in Cognitive ScienceML2.74https://www.cambridge.org/core/journals/theory-and-practice-of-logic-programming
Applied System InnovationML, Specific2.73https://www.journals.elsevier.com/physics-of-life-reviews
IET Cyber-Physical Systems: Theory and ApplicationsML2.72https://www.springer.com/journal/10590
ACM Transactions on Interactive Intelligent SystemsML2.47https://www.springer.com/journal/11023
Networks and Spatial EconomicsML, Specific2.4https://www.springer.com/journal/10846
Knowledge Engineering ReviewML2.39https://www.springer.com/journal/11370
Physics of Life ReviewsComp. Math, ML, Specific2.38https://www.nowpublishers.com/MAL
KybernetesML2.38http://ijfs.usb.ac.ir/
Cognitive ScienceML2.35https://www.emerald.com/insight/publication/issn/0368-492X
Argument and ComputationComp. Math, ML2.28https://www.iospress.nl/journal/international-journal-of-knowledge-based-and-intelligent-engineering-systems/
Cybernetics and SystemsML2.24https://www.mdpi.com/journal/robotics
Iranian Journal of Fuzzy SystemsML, Specific2.24https://www.sciencedirect.com/journal/journal-of-parallel-and-distributed-computing
Journal of HeuristicsML2.24https://www.springer.com/journal/10994
Journal of SchedulingML2.2http://journals.cambridge.org/action/displayJournal?jid=KER
IEEE Transactions on GamesML, Specific2.18https://onlinelibrary.wiley.com/journal/14678640
Journal of Intelligent SystemsML2.16https://www.springer.com/journal/146
International Journal of Advanced Robotic SystemsML2.15https://www.springer.com/journal/10817
Machine TranslationML, NLP2.15???
Journal of PragmaticsML2.11https://www.tandfonline.com/toc/uaai20/current
Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAMML2.04http://www.ijfis.org/main.html
Natural Language EngineeringML, NLP2.03https://onlinelibrary.wiley.com/journal/15516709
Spatial Information ResearchML2???
Journal of Intelligent and Fuzzy SystemsML, Specific1.95https://www.tandfonline.com/toc/ucbs20/current
KI - Kunstliche IntelligenzML1.91https://www.degruyter.com/view/journals/jisys/jisys-overview.xml
International Journal of Swarm Intelligence ResearchML1.86https://academic.oup.com/jos
International Journal of Intelligent Robotics and ApplicationsML1.81https://dl.acm.org/journal/tiis
Theory and Practice of Logic ProgrammingComp. Math, ML1.73https://aaai.org/Magazine/magazine.php
International Journal of Knowledge and Systems ScienceML1.69https://www.tandfonline.com/loi/lnfa20
Journal on Data SemanticsCV, ML, NLP, Signal1.68http://www.nnw.cz/
International Journal of Pattern Recognition and Artificial IntelligenceCV, ML1.67https://www.worldscientific.com/worldscinet/ijait
Journal of Automated ReasoningComp. Math, ML, Specific1.66https://www.journals.elsevier.com/cognitive-systems-research
Bulletin of the Polish Academy of Sciences: Technical SciencesML1.66https://www.journals.elsevier.com/journal-of-pragmatics
International Journal of Humanoid RoboticsML, Specific1.6https://www.worldscientific.com/worldscinet/ijprai
Neural Network WorldML1.57https://www.fujipress.jp/jaciii/jc/
Cognitive ProcessingML1.45https://www.worldscientific.com/worldscinet/ijufks
Adaptive BehaviorML1.44https://www.worldscientific.com/worldscinet/ijhr
AI CommunicationsML1.37http://journals.pan.pl/dlibra/journal/119067
International Journal of Software InnovationML1.34https://journal.iberamia.org/index.php/intartif/index
International Journal on Artificial Intelligence ToolsML1.33https://www.worldscientific.com/worldscinet/ijseke
International Journal of Fuzzy Logic and Intelligent SystemsML1.31http://www.springer.com/computer+science/ai/journal/10472
International Journal of Software Engineering and Knowledge EngineeringML1.31https://www.aicommunications.eu/
Intelligent Data AnalysisCV, ML1.3https://www.tandfonline.com/loi/tfie20
Annals of Mathematics and Artificial IntelligenceComp. Math, ML1.3https://journals.sagepub.com/home/adb
International Journal of Robotics and AutomationML, Specific1.25https://www.iospress.nl/journal/intelligent-data-analysis/
Informatica (Slovenia)ML1.21https://www.worldscientific.com/worldscinet/ijsc
International Journal of Cognitive Informatics and Natural IntelligenceML1.19???
Parallel ComputingML1.16???
International Journal of Uncertainty, Fuzziness and Knowlege-Based SystemsML1.15https://www.journals.elsevier.com/parallel-computing
Intelligenza ArtificialeML1.13https://www.kybernetika.cz/
Journal of SemanticsML1.12https://constructivist.info/
Inteligencia ArtificialML0.95https://www.igi-global.com/journal/international-journal-swarm-intelligence-research/1149
Web IntelligenceML0.95https://www.springer.com/journal/10015
Automatic Control and Computer SciencesComp. Math, ML0.93https://digital-library.theiet.org/content/journals/iet-spr
ConstraintsComp. Math, ML0.88https://www.iospress.nl/journal/journal-of-intelligent-fuzzy-systems/
IEICE Transactions on Information and SystemsML0.88https://journals.agh.edu.pl/csci
International Journal of Semantic ComputingML0.84https://www.jstage.jst.go.jp/browse/transinf
Artificial Life and RoboticsML0.84https://www.iospress.nl/journal/intelligenza-artificiale/
Computer ScienceML0.83https://www.iospress.nl/journal/web-intelligence-and-agent-systems/
International Journal of Knowledge-Based and Intelligent Engineering SystemsML0.81http://journals.cambridge.org/action/displayJournal?jid=AIE
KybernetikaML0.8http://cogsci.snu.ac.kr/jcs/
ComputabilityComp. Math, ML0.71https://www.springer.com/computer/database+management+%26+information+retrieval/journal/13740
Journal of Advanced Computational Intelligence and Intelligent InformaticsML0.53https://www.igi-global.com/journal/international-journal-software-innovation/64245
Journal of Robotics, Networking and Artificial LifeML0.49???
Fuzzy Information and EngineeringML0.45http://www.informatica.si/index.php/informatica
Computer Science Journal of MoldovaML0.43https://www.igi-global.com/journal/international-journal-knowledge-systems-science/1169
Journal of Cognitive ScienceML0.39https://www.igi-global.com/journal/international-journal-cognitive-informatics-natural/1095
Constructivist FoundationsML0.36https://www.tandfonline.com/action/journalInformation?journalCode=tssc20
Medical Image AnalysisCV, Specific15.24https://www.journals.elsevier.com/journal-of-visual-communication-and-image-representation
International Journal of Computer VisionCV, ML11.81https://www.journals.elsevier.com/pattern-recognition-letters
Computerized Medical Imaging and GraphicsCV8.4https://www.springer.com/journal/12065
IEEE Transactions on Visualization and Computer GraphicsCV, Signal5.56https://www.frontiersin.org/journals/neurorobotics
Cognitive ComputationCV5.24https://www.springer.com/journal/40815
International Journal on Document Analysis and RecognitionCV, NLP4.4https://onlinelibrary.wiley.com/journal/10981098
Signal Processing: Image CommunicationCV, Signal3.97http://computeroptics.smr.ru/eng/index.html
International journal of computer assisted radiology and surgeryCV3.77https://digital-library.theiet.org/content/journals/iet-cvi
Journal of Visual Communication and Image RepresentationCV, Signal3.5https://www.springer.com/journal/10506
Journal of ImagingCV3.43???
Computer OpticsCV3.26https://www.springer.com/journal/13042
Information VisualizationCV3.23https://journals.sagepub.com/home/ivi
Machine Vision and ApplicationsCV3.05https://www.journals.elsevier.com/international-journal-of-approximate-reasoning
International Journal of Imaging Systems and TechnologyCV2.88https://www.journals.elsevier.com/speech-communication
Pattern Analysis and ApplicationsCV, ML2.76https://www.springer.com/journal/13748
Journal of the Optical Society of America A: Optics and Image Science, and VisionCV2.25https://www.springer.com/journal/10462
Spatial Cognition and ComputationCV1.88https://www.journals.elsevier.com/computers-and-graphics
Computers and GraphicsCV, Signal1.88https://www.journals.elsevier.com/artificial-intelligence-in-medicine
Journal of Mathematical Imaging and VisionCV, Comp. Math1.67https://www.springer.com/journal/10514
IET Computer VisionCV1.64https://tist.acm.org/
Pattern Recognition and Image AnalysisCV, ML1.24https://www.springer.com/journal/11493
Imaging Science JournalCV1.17https://www.tandfonline.com/loi/yims20
Journal of Computer and Systems Sciences InternationalCV, ML1.04https://www.springer.com/journal/11488
International Journal of Image and GraphicsCV0.92https://www.worldscientific.com/worldscinet/ijig
Intelligent Decision TechnologiesCV, ML0.74https://www.iospress.nl/journal/intelligent-decision-technologies/
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IEEE Signal Processing MagazineSignal9.72https://iopscience.iop.org/journal/0266-5611
Mechanical Systems and Signal ProcessingSignal9.09https://benjamins.com/catalog/ijcl
IEEE Journal on Selected Topics in Signal ProcessingSignal8.93https://www.springer.com/computer/journal/11714?detailsPage=aboutThis
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IEEE/ACM Transactions on Audio Speech and Language ProcessingComp. Math, Signal6.02https://tsas.acm.org/
Computer Vision and Image UnderstandingCV, Signal5.53https://www.journals.elsevier.com/mathematics-and-computers-in-simulation
IEEE Transactions on Signal ProcessingSignal5.27https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=97
Signal ProcessingCV, Signal4.99https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=2945
Image and Vision ComputingCV, Signal4.63https://www.springer.com/journal/40998
Journal of the Franklin InstituteSignal4.48https://ieeexplore.ieee.org/xpl/aboutJournal.jsp?punumber=6884276
APSIPA Transactions on Signal and Information ProcessingSignal4.3https://www.ipol.im/
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IEEE Transactions on Control of Network SystemsSignal3.77https://www.springer.com/journal/11760
IEEE Signal Processing LettersSignal3.67https://jivp-eurasipjournals.springeropen.com
IEEE Transactions on Signal and Information Processing over NetworksSignal3.59http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=71
International Journal of Adaptive Control and Signal ProcessingSignal3.54https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=78
Electronics (Switzerland)Signal3.27https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=93
Eurasip Journal on Image and Video ProcessingSignal3.24https://www.sciencedirect.com/journal/information-fusion
Frontiers of Information Technology and Electronic EngineeringSignal3.05https://www.nowpublishers.com/SIG
Foundations and Trends in Signal ProcessingSignal3https://www.mdpi.com/journal/electronics
Circuits, Systems, and Signal ProcessingComp. Math, Signal2.72https://www.springer.com/journal/11128
Multidimensional Systems and Signal ProcessingComp. Math, ML, Signal2.37https://www.springer.com/journal/34
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ACM Transactions on Spatial Algorithms and SystemsSignal2.23https://www.springer.com/journal/11045
IET Image ProcessingCV, Signal2.2https://www.sciencedirect.com/journal/computer-vision-and-image-understanding
Eurasip Journal on Advances in Signal ProcessingSignal2.1https://www.cambridge.org/core/journals/apsipa-transactions-on-signal-and-information-processing
IET Signal ProcessingSignal1.99http://ieee-iotj.org/
Signal, Image and Video ProcessingSignal1.97https://www.sciencedirect.com/journal/journal-of-the-franklin-institute
Quantum Information ProcessingSignal, Specific1.91https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6509490
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Mathematics of Control, Signals, and SystemsComp. Math, Signal1.61https://www.tandfonline.com/loi/tinf20
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Image Processing On LineCV, Signal1.39https://www.springer.com/journal/11265
INFORSignal1.27https://asp-eurasipjournals.springeropen.com/
Information Processing LettersSignal1.14https://www.journals.elsevier.com/image-and-vision-computing
Computer Assisted Language LearningNLP5.74https://www.springer.com/journal/10579
Language Learning and TechnologyNLP4.57https://www.iospress.nl/journal/applied-ontology/
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Journal of Memory and LanguageML, NLP4.07https://www.journals.elsevier.com/computerized-medical-imaging-and-graphics
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International Journal of Speech TechnologyCV, NLP, Signal1.94https://www.cambridge.org/core/journals/recall
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International Journal of Corpus LinguisticsNLP1.13https://www.springer.com/journal/10772
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IEEE Internet of Things JournalCV, ML, Signal, Specific10.98???
IEEE Transactions on Evolutionary ComputationComp. Math15.5https://www.springer.com/journal/12351/
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International Journal of Artificial Intelligence in EducationComp. Math4.82http://www.ijfis.org/main.html
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International Journal of Automation and ComputingComp. Math4.28https://www.iospress.nl/journal/informatica/
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Foundations of Computational MathematicsComp. Math3.12https://www.siam.org/publications/journals/siam-journal-on-scientific-computing-sisc
Computers and Mathematics with ApplicationsComp. Math3.11https://www.tandfonline.com/toc/gcom20/current
Computational and Applied MathematicsComp. Math3.09https://www.siam.org/publications/journals/siam-journal-on-numerical-analysis-sinum
Computational and Mathematical Organization TheoryComp. Math3.06https://www.tandfonline.com/toc/tsma20/current
Computational and Mathematical Methods in MedicineComp. Math3https://www.journals.elsevier.com/journal-of-combinatorial-theory-series-a
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International Journal of Intelligent Transportation Systems ResearchComp. Math2.27https://academic.oup.com/jssam
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Inverse ProblemsComp. Math, Signal2.22https://www.journals.elsevier.com/mechanical-systems-and-signal-processing/
Measurement Science and TechnologyComp. Math2.21https://www.springer.com/journal/10255
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Concurrency Computation Practice and ExperienceComp. Math2.18https://www.journals.elsevier.com/journal-of-complexity
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ACM Transactions on Parallel ComputingComp. Math2.05http://mia.ele-math.com/
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Advances in Calculus of VariationsComp. Math1.84https://www.springer.com/journal/10623
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Advances in Fuzzy SystemsComp. Math1.78https://www.springer.com/journal/40314
Bulletin of the American Mathematical SocietyComp. Math1.76http://www.springer.com/engineering/journal/11831
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Stochastic Processes and their ApplicationsComp. Math1.51https://journals.sagepub.com/home/sdj
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Discrete and Continuous Dynamical SystemsComp. Math1.47https://www.journals.elsevier.com/journal-of-mathematical-analysis-and-applications
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Applied MathematicsComp. Math0.8https://www.degruyter.com/view/j/jaa?lang=en
International Journal of Modelling, Identification and ControlComp. Math0.8https://www.springer.com/journal/10440
Acta Mathematica Sinica, English SeriesComp. Math0.8https://www.springer.com/engineering/electronics/journal/13177
Applied Mathematics E - NotesComp. Math0.79https://mmp.susu.ru/page/en/greet
Bulletin of Computational Applied MathematicsComp. Math0.78http://www.math.nthu.edu.tw/~amen/
OrderComp. Math0.76https://www.begellhouse.com/journals/computational-thermal-sciences.html
Communications in Mathematics and StatisticsComp. Math0.73https://www.journals.elsevier.com/applied-numerical-mathematics/
Applicable Algebra in Engineering, Communications and ComputingComp. Math0.72???
Journal of Modern DynamicsComp. Math0.68https://www.springer.com/journal/12346
Journal of Applied AnalysisComp. Math0.67http://www.cai.sk/ojs/index.php/cai
Electronic Journal of Graph Theory and ApplicationsComp. Math0.66https://mcfns.net/index.php/Journal
Electronic Journal of CombinatoricsComp. Math0.63???
Acta Mathematicae Applicatae SinicaComp. Math0.62https://www.degruyter.com/view/journals/acv/acv-overview.xml
Mathematics in Computer ScienceComp. Math0.54https://www.springer.com/journal/11634
Dependence ModelingComp. Math0.52https://www.aimsciences.org/journal/A0000-0000
Journal of Computational Methods in Sciences and EngineeringComp. Math0.48https://www.springer.com/journal/11766
Mathematical and Computational Forestry and Natural-Resource SciencesComp. Math0.47https://www.degruyter.com/view/journals/ijnsns/ijnsns-overview.xml
Journal of Applied Mathematics and InformaticsComp. Math0.47https://www.iospress.nl/journal/journal-of-computational-methods-in-sciences-and-engineering/
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+ + diff --git a/materials/nir/index.html b/materials/nir/index.html new file mode 100644 index 00000000..5e164a1d --- /dev/null +++ b/materials/nir/index.html @@ -0,0 +1,2262 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Research Reports + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + +

2024 FALL

+ +

Postgraduate Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + +
Postgraduate studentYearPhD thesis topicScientific adviserLink to publication
Viktor Pankratov2Probabilistic topic modelingVorontsov K.V.Paper,Code,Slides
Konstantin Yakovlev1Tensor Methods in Federated LearningGasnikov A.V.Publication 1, Publication 2
+ +

Second Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Galina Boeva2Efficient aggregation by labels for the problem of event sequencesZaytsev A. A.Publication, Paper, Slides, Code
Nikita Kornilov2Optimal Flow Matching: Learning Straight Trajectroies in Just One StepGasnikov A.V.Publication, Paper, Slides, Code
+ +

First Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearTopicScientific adviserLink to publication
Nikita Kiselev1Unraveling the Hessian: A Key to Smooth Convergence in Loss Function LandscapesGrabovoy A.V.Paper, Code, Slides
Daniil Dorin1Декодирование визуальных стимулов из мультимодальных сигналов мозгаGrabovoy A.V.Publication, Paper1, Paper2, Code1, code2, Slides
Kirill Semkin1Time series classification in parameters space using NeuralODEStrijov V.V.Paper,Code,Slides,
Andrey Veprikov1The optimal control problem in artificial intelligence systems with feedback loopKhritankov A.S.Paper, Code,Slides
Ilgam Latypov1γ-Competitiveness: An Approach to Multi-Objective Optimization with High Computation Costs in Lipschitz FunctionsDorn Y.V.Paper, Code, Slides
Ignashin Igor1Stochastic Correspondences Frank-WolfeGrabovoy A.V.Paper, Code, Slides
+ +

Fourth Year Bachelor Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Papay Ivan4Ordinal Classification Using Partially Ordered Feature SetsStrijov V.V.Code Paper Slides
Meshkov Vladislav4ConvNets Landscape Convergence: Hessian-Based Analysis of Matricized NetworksGrabovoy A.V.Paper, Code, Slides
Stepanov Ilia4The use of synthetic data obtained using a generative neural network to improve the quality of detection modelsGrabovoy A.V.Paper, Code, Slides
Nabiev Muhammadsharif4Inductive Bias in Model SelectionBakhteev O. Y.Paper, Code, Slides
Zadvornov Egor4Forecasting social trends with high volatilityMalkov A. S.Paper, Code, Slides
Rebrikov Aleksei4Investigation of Neural Network Sparsification Mechanisms Based on Weight ImportanceBeznosikov A.N.Paper, Code, Slides
Firsov Sergey4Neural architecture search with target hardware controlBakhteev O. Y.Paper, Code, Slides
+ +

2024 SPRING

+

Postgraduate Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Postgraduate studentYearPhD thesis topicScientific adviserLink to publication
Vasiliy Alekseev4Incompleteness and Instability of Topic ModelsVorontsov K.V.Paper1, Paper2, Paper3; Slides1, Slides2
Novitskii Vasilii3New Bounds for One-point Oracle in Stochastic Gradient-free OptimizationGasnikov A.V.Paper 1, Paper 2, Paper 3, Slides, Code, Text
Alexey Grishanov2Applying Reinforcement Learning for Recommendation Platform PersonalizationVorontsov K.V.Paper 1, Paper 2, Code, Slides
Panchenko Sviatoslav2Graph diffusion models for the task of brain signal decodingStrijov V.V.Code, Slides, Paper1
Pavel Severilov2Decoding of multimodal signals of brain activityStrijov V.V.Paper1 Paper2 Thesis, Code, Slides Paper1
Denis Tikhonov2Attractor reconstruction for linearized system with miltilinear mapStrijov V.V.Code, Slides Paper1
Viktor Pankratov1Probabilistic topic modelingVorontsov K.V.Paper,Code,Slides
+ +

Second Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Klypa Roman2Generative modeling for protein structure and interactionsGrudinin S.V.Paper, Slides, Code
Kovaleva Maria2Addition of external information for enhancement of local embeddings for event sequences data modelsZaytsev A. A.Paper, Thesis, Slides, Code
Ksenofontov Gregory2Adversarial Schrödinger BridgesRoman IsachenkoCode, Slides, Draft, Draft
Konstantin Yakovlev2Concordant Neural Architecture Search on Multidomain DataBakhteev O. Y.Paper, Slides, Code
Tolmachev Alexander2Information Bottleneck Analysis of Deep Neural NetworksAlexey FrolovPaper, Paper2, Slides
Polina Barabanshchikova2Tverberg type theoremsPolyanskii A.A.Draft, Slides, Code
Alkin Emil2Expressive Power of Recurrent Neural Networks, IIIvan OseledetsDraft, Slides, Code
+ +

First Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Boeva Galina1Label Attention Network for Temporal Sets predictionZaytsev A. A.Full Paper Paper, Slides, Code
Chumachenko Arina1Machine learning methods for functional brain mappingSharaev M. G.Paper, Slides, Code
Marat Khusainov1Adaptive sampling methods using diffusion modelsSamsonov S.V.Paper, Slides , Code
Kornilov Nikita1Optimal Flow MatchingGasnikov A.V.Paper, Slides, Code
Kseniia Petrushina1Quantifying image realism via language model reasoningsAlexander PanchenkoPaper, Slides , Code
Parviz Karimov1Representation learning for collections of dataIsachenko R.V.Paper, Slides, Code
Dmitry Protasov1Automatic Music TranscriptionIvan MatveevPaper, Slides, Code
German Gritsai1Automatic Detection of Machine Generated TextsGrabovoy A. V.Paper 1, Paper 2, Slides
+ +

Fourth Year Bachelor Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Nikita Kiselev4Bayesian Sample Size EstimationGrabovoy A. V.Thesis, Paper 1, Code 1, Paper 2, Code 2, Slides
Andrey Veprikov4A Mathematical Model of the Hidden Feedback Loop Effect in Machine Learning SystemsKhritankov A.S.Paper, Code, Slides
Ilgam Latypov4Balancing Efficiency and Interpretability: A New Approach to Multi-Objective Optimization with High Computation Costs in Lipschitz FunctionsDorn Y.V.Paper, Code, Slides
Anna Remizova4reducing the dimension of the space of the trainable parameters in the domain adaptation problemGrabovoy A. V.Paper, Code, Slides
Anastasia Voznyuk4Detection of machine-generated fragments based on text style change analysisGrabovoy A. V.Paper, Code, Slides
Dorin Daniil4Spatial-temporal characteristics in the time series decodingGrabovoy A. V.Paper 1, Code 1, Paper 2, Code 2, Slides
Semkin Kirill4Tensor decomposition and forecast for multidimensional time seriesStrijov V.V.Paper, Code, Slides
Nikitina Maria4Analysis of distribution bias in contrastive learningIsachenko R.V.Paper, Code, Slides
Babkin Petr4Differential Neural Ensemble Search with Diversity ControlBakhteev O.Yu.Paper, Code, Slides
Ignashin Igor4Bayesian distillation of transformer-based modelsGrabovoy A. V.Paper, Code, Slides
Terentyev Alexander4Classification of trajectories of dynamic systems using physically-informed neural networksStrijov V.V.Paper, Code, Slides
Matvei Kreinin4Methods with preconditioning and weight decayingBeznosikov A.N.Paper, Code, Slides
Alexander Bogdanov4Application of zero-order stochastic approximation with memoization technique in the Frank-Wolfe algorithmBeznosikov A.N.Paper, Code, Slides
Okhotnikov Nikita4Interconnected latent representations for outfit generation taskIsachenko R.V.Paper, Code, Slides
Oleinik Mikhail4Knowledge distillation in deep neural networks using model structure alignment methodsBakhteev O.Y.Paper, Code, Slides
+ +

2023 FALL

+ +

Postgraduate Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Postgraduate studentYearPhD thesis topicScientific adviserLink to publication
Viktor Pankratov1Probabilistic topic modelingVorontsov K.V.Paper,Code,Slides
Pavel Severilov2Decoding of multimodal signals of brain activityStrijov V.V.Paper, Code, Slides
Alexey Grishanov2Applying Reinforcement Learning for Recommendation Platform PersonalizationVorontsov K.V.Paper 1, Paper 2 - under review, Code, Slides
Novitskii Vasilii3New Bounds for One-point Oracle in Stochastic Gradient-free OptimizationGasnikov A.V.Paper 1, Paper 2, Paper 3, Slides, Code
Vasiliy Alekseev4Incompleteness and Instability of Topic ModelsVorontsov K.V.Conf1 (Slides1), Slides2
Tikhonov Denis2Dimensionality reduction of tensor phase spaces in nonlinear dynamical system reconstructionStrijov V.V.(Slides), Code
Panchenko Sviatoslav2Graph Diffusion models for human brain activity decodingStrijov V.V.Paper, Slides, Code
+ +

Second Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Rustem Islamov2Distributed Newton-Type Methods with Communication Compression and Bernoulli AggregationStrijov V.V., Richtarik P.Paper, Code, Slides
Kovaleva Maria2Addition of global information for enhancement of local embeddings for transactional data modelsZaytsev A.APaper, Slides
Tolmachev Alexander2Information Bottleneck Analysis of Deep Neural NetworksAlexey FrolovPaper, Slides
Klypa Roman2Generative modeling for protein structure and interactionsGrudinin S.V.Slides, Code
Polina Barabanshchikova2Tverberg type theoremsPolyanskii A.A.Paper, Slides
Konstantin Yakovlev2Concordant Neural Architecture Search on Multidomain DataBakhteev O. Y.Paper, Slides, Code
Ksenofontov Gregory2Adversarial Schrödinger BridgesRoman IsachenkoCode, Slides, Draft
Alkin Emil2Expressive Power of Recurrent Neural Networks, IIIvan OseledetsDraft, Slides, Code
+ +

First Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearTopicScientific adviserLink to publication 
Yakovlev Konstantin1Concordant Neural Architecture Search on Multidomain DataBakhteev O. Y.Paper, Code, Slides 
Galina Boeva1Identifying the relationship between labels using an attention-based algorithm for the Next Basket Recommendation taskZaytsev A.APaper Code Slides 
Bair Mikhailov1Undersampled MRI ReconstructionDylov D.VSlides 
Pavel Bartenev1MRI data augmentation via conditional generative 3D inpaintingMaxim SharaevSlides Code 
Kseniia Petrushina1Detection of hallucinations of language modelsAlexander PanchenkoSlides Code 
Arina Chumachenko1Machine learning methods for functional brain mappingMaxim SharaevSlidesCode
Nikita Kornilov1Intermediate Gradients Methods with Relative InexactnessAlexandr GasnikovSlides Code Paper 
Dmitry Protasov1Automatic Music TranscriptionIvan MatveevSlides Code Draft 
Parviz Karimov1Representation learning for data point groupsRoman IsachenkoSlides Draft 
Eduard Vladimirov1Adversarial attacks on neural networks for time seriesZaytsev A.ASlides Code Draft 
Zharov Georgiy1Search for an effective architecture for solving the problem of obtaining multimodal embeddings for three or more modalities Slides Code 
+ +

Fourth Year Bachelor Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Antyshev Tikhon4Gradient Sliding for Saddle Point problems with one compositeGasnikov A. V.Code Paper Slides
Kiselev Nikita4Bayesian Sample Size EstimationGrabovoy A. V.Paper, Code, Slides
Kreinin Matvei4On methods with preconditioning and weight decayingBeznosikov A. N.Paper, Code, Slides
Ilgam Latypov4Research On multicriteria optimization using Shapley ValueDorn Y.V.Paper, Code, Slides
Anastasiia Vozniuk4Detection of Machine-Generated Fragments in TextGrabovoy A.V.Paper, Code, Slides
Terentyev Alexander4Classification of trajectories of dynamic systems with physics-informed neural networksStrijov V.V.Paper, Code, Slides
Veprikov Andrey4A mathematical model of the hidden feedback loop effects in machine learning systemsKhritankov A.S.Paper, Code, Slides
Ignashin Igor4Bayesian distilation of transformer-based modelsGrabovoy A.V.Paper, Code, Slides
Remizova Anna4Altering latent representation in the audio style transfer taskGrabovoy A.V.Paper, Code, Slides, Paper handwritten draft
Babkin Petr4Differential neural ensemble search with diversity controlBakhteev O.Y.Paper, Code, Slides
Nikitina Maria4Analysis of distribution bias in contrastive learningIsachenko R.V.Paper, Code, Slides
Oleinik Mikhail4Knowledge distillation in deep neural networks using model structure alignment methodsBakhteev O.Y.Paper, Code, Slides
Semkin Kirill4Tensor-SSA method in application to time series decompositionStrijov V.V.Paper, Code, Slides
Bogdanov Alexander4New Aspects of Black Box Conditional Gradient: Variance Reduction and One Point FeedbackBeznosikov A. N.Paper, Code, Slides
Dorin Daniil4Spatial-temporal characteristics in the time series decodingGrabovoy A. V.Paper, Code, Slides
Okhotnikov Nikita4Interconnected latent representations for outfit generation taskIsachenko R.V.Paper, Code, Slides
+ +

2023 SPRING

+ +

Postgraduate Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Postgraduate studentYearPhD thesis topicScientific adviserLink to publication
Pavel Severilov1Decoding of multimodal signals of brain activityStrijov V.V.Code, Slides
Grishanov Alexey1Applying Reinforcement Learning for Recommendation Platform PersonalizationVorontsov K.V.Paper, Code, Slides
Panchenko Sviatoslav1Graph Diffusion Models for the Task of Signal DecodingStrijov V.V.Paper (Translated, draft), Code, Slides (IDP conf.)
Vasilii Novitskii2New Bounds for One-point Oracle in Stochastic Gradient-free OptimizationGasnikov A.V.Paper 1, Paper 2, Slides, Code
Alina Samokhina2Continous-in-time representations of signalsStrijov V.V.Code old, Paper draft, Slides
Vasiliy Alekseev3Incompleteness and Instability of Topic ModelsVorontsov K.V.Paper (draft), Slides
Aleksei Goncharov4Space-time series alignment modelsStrijov V.V.Papers, Slides, Thesis
Petr Ostroukhov4Tensor Methods for Convex Functions MinimizationGasnikov A.V.Paper, Slides
Denis Kuznetsov4Neural network models of dialogue on general topicsBurtsev M.S.Paper with Code
Radoslav Neychev4Informative prior in privileged learningStrijov V.V.Old paper, Paper 1, New paper 2 (in blind review for now)
+ +

Second Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Rustem Islamov2Distributed Newton-Type Methods with Communication Compression and Bernoulli AggregationStrijov V.V., Richtarik P.Paper, Code, Slides
Filatov Andrei2Text interfaces for event sequencesStrijov V.V.Paper, Slides
Shokorov Viacheslav2Bootstrapping of neural network ensemblesVetrov D.P.Text (draft) Slides, Code
Safiullin Robert2Multimodel representation of dynamic systemsStrijov V.V.Paper Slides, Code
Bishuk Anton2Controlled Graph GenerationZukhba A.V.Paper, Code, Slides
Pankratov Viktor2Probabilistic topic modelingVorontsov K.V.Paper, Code, Slides
Grebenkova Olga2Automatic detection of focal cortical dysplasia for sparse data representationBurnaev EDraft, Code, Slides Paper
Nadezhda Alsahanova2Selection of tensor representations for multiview forecastingStrijov V.V.Draft, Code, Slides
+ +

First Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearTopicScientific adviserLink to publication
Yakovlev Konstantin1Concordant Neural Architecture Search on Multidomain DataBakhteev O. Y.Paper, Code, Slides
Kovaleva Maria1Neural architecture search with early stoppingAlexey ZaytsevCode, Slides, Draft
Ksenofontov Gregory1Analysis of generative modeling methods based on Schrödinger bridgesRoman IsachenkoCode, Slides, Draft
Polina Barabanshchikova1Helly type problems for d-intervalsPolyanskii A.A.Paper, Slides
Tolmachev Alexander1Information Bottleneck Analysis of Deep Neural NetworksAlexey FrolovPaper, Slides
Alkin Emil1Expessive Power of Recurrent Neural NetworksOseledets I. V.Slides, Code
+ +

Fourth Year Bachelor Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Antyshev Tikhon4Gradient Sliding for Saddle Point problems with one compositeGasnikov A. V.Code Paper Slides
Kornilov Nikita4Gradient Free Methods for Non-Smooth Convex Stochastic Optimization with Heavy Tails on Convex CompactGasnikov A. V.Code Paper Slides
Lukyanenko Ivan4Detection of manipulations and its targets in news textsVorontsov K.V.Code, Text, Slides
Zharov Georgiy4Classification of manipulative fragments in news textsVorontsov K.V.Code, Slides
Vladimirov Eduard4Choosing a state space model in a neural decoding problemStrijov V.V.Code1, Code2, Slides
Molozhavenko Alexander4Solution of a block multidimensional eigenvalues search problemGasnikov A.V.Slides, Code
+ +

2022 AUTUMN

+ +

Postgraduate Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Postgraduate studentYearPhD thesis topicScientific adviserLink to publication
Vasiliy Alekseev3Incompleteness and Instability of Topic ModelsVorontsov K.V.Paper, Paper (conf.)
Grishanov Alexey1Applying Reinforcement Learning for Recommendation Platform PersonalizationVorontsov K.V.Paper, Code, Slides (Sber AI Lab seminar)
Panchenko Sviatoslav1Graph Diffusion Models for the Task of Signal DecodingStrijov V.V.Paper (Article, draft), Code, Slides (IDP conf.)
Denis1Dimension reduction of tensor phase spaces in dynamical system simulationStrijov V.V.Paper, Code, Slides
Alina Samokhina2Continous-in-time representations of signalsStrijov V.V.Code old, Paper published, Paper draft, Slides
Vasilii Novitskii2New Bounds for One-point Oracle in Stochastic Gradient-free OptimizationGasnikov A.V.Paper 1, Paper 2, Slides, Code
Polina Potapova3Topic modeling for multilingual topic searchVorontsov K.V.Paper, Code
     
+ +

Second Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Andrei Filatov2Infinite transformersStrijov V.V.Paper, Code, Slides
Rustem Islamov2Distributed Newton-Type Methods with Communication Compression and Bernoulli AggregationStrijov V.V., Richtarik P.Paper, Code, Slides
Bishuk Anton2Controlled Graph GenerationZukhba A.V.Paper, Code, Slides
Grebenkova Olga2Automated detection of focal cortical dysplasiaBurnaev ESlides Acceptance letter
Safiullin Robert2Multimodel representation of dynamic systemsStrijov V.V.Paper, Code, Slides
Shokorov Viacheslav2Deep ensembles bootstrappingVetrov D.P.Notes, Code
Pankratov Viktor2Probabilistic topic modelingVorontsov K.V.Paper, Code, Slides
Alsahanova Nadezhda2Selection of tensor representations for multiview forecastingStrijov V.V.Paper, Code, Slides
+ +

First Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearTopicScientific adviserLink to publication
Maria Kovaleva1Research of efficient transformersAlexey ZaytsevPaper, Code, Slides
Roman Klypa1Combination of geometrical learning and language models for bioinformaticsGrudinin S.V.Slides
Polina Barabanshchikova1Helly type problems for d-intervalsPolyanskii A.A.Paper, Slides
Ksenofontov Gregory1Creating a personalized avatar of a person for a virtual fitting of clothesVorontsov K.V., Yanina A.O.Slides
Yakovlev Konstantin1Concordant Neural Architecture Search on multi-domain dataBakhteev O.Y.Slides
+ +

Fourth Year Bachelor Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Eduard Vladimirov4Ways to account for data noise in a Neural ODE modelStrijov V.V.Paper, Code, Slides
Antyshev Tikhon4Zero-order Mirror Descent for Saddle Point ProblemsGasnikov A.V.Paper, Code, Slides
Ivan Lukyanenko4Joint NER and RE in manipulation newsVorontsov K.V.Code Slides
Kornilov Nikita4Gradient Free Optimization with Infinite VarianceGasnikov A.V.Paper, Slides
Georgiy Zharov4Search for manipulations and their relations with named entities in textsVorontsov K.V.Slides
Molozhavenko Alexander4Solution of a block multidimensional eigenvalues search problemGasnikov A.V.Slides, Code
+ +

2022 SPRING

+ +

Postgraduate Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Postgraduate studentYearPhD thesis topicScientific adviserLink to publication
Andrey Grabovoy1Bayesian DistilationStrijov V.V.Code, Thesis
Alina Samokhina1Continous-time representation for signal decodingStrijov V.V.Code, Paper, Slides
Nikitin Filipp2Generation and selection of graph neural network models in the problem of organic chemistryStrijov V. V.Code
Polina Potapova2Topic modeling for multilingual topic searchVorontsov K.V.Paper, Code
Vasiliy Alekseev2Incompleteness and Instability of Topic ModelsVorontsov K.V.Paper (not visible), Code (private)
Ostroukhov Petr3Tensor methods for convex optimizationGasnikov A.V.Paper 1, Paper 2
Kamil Safin3Combined methods for text plagiarism detectionChehovich Y.V.Paper
Denis Kuznetsov3Neural network models of dialogue on general topicsBurtsev M.S.Paper_1, Paper_2
Ilia Zharikov4Neural network methods for document image recognitionVorontsov K.V.Paper, Code, Slides
Alex Goncharov3Space-time series alignment modelsStrijov V.V.Papers, Slides
+ +

Second Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Petr Mokrov2Wasserstein gradient flows: modeling and applicationsBurnaev E.V.Paper, Code, Slides
Denis Tikhonov2Quasiperiodic time signals classification with spherical harmonicsStrijov V.V.Paper, Code, Slides
Natalia Varenik2Building a connectivity map of functional groups in the problem of decoding brain signalsStrijov V.V.Paper, Code, Slides
Alexey Grigorev2Regularization of neural layer via construction of frame in parameter spaceGneushev A.N.Slides, Code, Paper
Kolesov Aleksandr2Adverasrial method for Transfer Learning based on Optimal TransportBakhteev O.YPaper, Code, Slides
Severilov Pavel2Choosing the optimal model in the problem of modeling dynamics of a physical system by neural networksStrijov V.V.Paper Slides Code Paper2
Panchenko Sviatoslav2Bilinearity of geometric product for the task of signal decodingStrijov V.V.Paper, Slides Code
Grishanov Alexey2Application of Reinforcement Learning for recommendation system personalizationVorontsov K.V.Paper, Slides, Сode
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First Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearTopicScientific adviserLink to publication
Rustem Islamov1Basis Matters: Better Communication-Efficient Second Order Methods for Federated LearningRichtarik P., Strijov V.V.Paper, Code, Slides
Bishuk Anton1Controlled graph generation using the variational autoencoder modelZukhba A.V.Report
Grebenkova Olga1Automated detection of focal cortical dysplasiaBurnaev EReport
Filatov Andrei1Novel view synthesisLempitsky VictorSlides Code
Safiullin Robert1Multimodel representation of dynamic systemsStrijov V.V.Paper, Code, Slides
Pankratov Viktor1Topic balancing of topic modelsVorontsov K.V.Code, Slides
Shokorov Viacheslav1Bootstrapping of neural network ensemblesVetrov D.P.Report Code
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Fourth Year Bachelor Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Mariya Gorpinich4Metaparameter optimization in knowledge distillationBakhteev O.Yu.Code, Slides, Paper
Vyacheslav Gorchakov4Importance Sampling Approach to Chance-Constrained DC Optimal Power FlowMaximov Y.V.Paper, Code, Slides
Antonina Kurdyukova4Dimensionality reduction of the phase space in canonical correlation analisysStrijov V.V., Isachenko R.V.Code, Slides, Paper
Anton Pilkevich4Optimization of the criterion given by the neural network model in the text detoxification taskStrijov V.V. (Popov A.S.)Code, Slides,Paper
Konstantin Yakovlev4Selection of concordant architectures with complexity controlBakhteev O.Y.Paper Code, Slides
Khristolyubov Maxim4Approximation of the phase trajectory of the time seriesStrijov V.V.Paper Code, Slides
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2021 FALL

+ +

Postgraduate Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Postgraduate studentYearPhD thesis topicScientific adviserLink to publication
Andrey Grabovoy1A prior distribution of parameters in problems of choosing deep learning modelsStrijov V.V.Paper, Code, Slides
Alina Samokhina1Continuous time representation for signal decodingStrijov V.V.Paper
Tamaz Gadaev1Multilinear model choice in forecasting problemStrijov V.V.Paper
Vasilii Novitskii1New Bounds for One-point Oracle in Stochastic Gradient-free OptimizationGasnikov A.V.Paper 1, Paper 2, Slides, Code
Vasiliy Alekseev2Incompleteness and Instability of Topic ModelsVorontsov K.V.Paper, Code, Slides1, Slides2
Polina Potapova2Topic modeling for multilingual topic searchVorontsov K.V.Paper
Petr Ostroukhov3Tensor methods for optimization of convex functionsGasnikov A.V.Paper
Denis Kuznetsov3Neural network models of dialogue on general topicsBurtsev M.S.Paper
Kamil Safin3Intrinsic methods for plagiarised texts detectionChehovich Y.V.Paper
Ilia Zharikov4Neural network methods for document image recognitionVorontsov K.V.Paper
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Second Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Petr Mokrov2Wasserstein gradient flows: modeling and applicationsBurnaev E.V.Paper, Code, Slides
Denis Tikhonov2Model selection for quasiperiodic time series forecastingStrijov V.V.Code, Slides
Alexey Grigorev2Regularization of neural layer via construction of frame in parameter spaceGneushev A.N.Slides, Code; Paper
Natalia Varenik2Building a connectivity map of functional groups in the problem of decoding brain signalsStrijov V.V.Paper Slides Code
Severilov Pavel2Differential analysis of phase spaces in the problem of decoding signalsStrijov V.V.Slides Code
Panchenko Sviatoslav2Bilinearity of geometric product for the task of signal decodingStrijov V.V.Slides
Grishanov Alexey2Application of Reinforcement Learning for recommendation system personalizationVorontsov K.V.Slides, Сode
Kolesov Aleksandr2Adversarial approach for transfer learningBahteev O.Yu.Paper, Slides, Сode
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First Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearTopicScientific adviserLink to publication
Rustem Islamov1Second Order Methods for Federated LearningRichtarik P, Strijov V.V.Paper, Code, Slides
Grebenkova Olga1Automated detection of focal cortical dysplasiaBurnaev EPaper, Code, Slides
Safiullin Robert1Substance properties analysis based on its SERS spectraStrijov V.V.Report, Slides
Pankratov Viktor1Topic balancing of topic modelsVorontsov K.V.Report,Code
Filatov Andrei1Task DiscoveryVictor Lempitsky Strijov V.V.Report
Bishuk Anton1Controlled graph generation using the variational autoencoder modelZukhba A.V.Report
Shokorov Viacheslav1Bootstrapping of neural network ensemblesVetrov D.P.Report Code
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Fourth Year Bachelor Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Antonina Kurdyukova4Phase detection of human motions with signals of wearable devicesStrijov V.V.Paper, Code, Slides
Anton Pilkevich4Clustering of news text messages based on polar opinionsVorontsov K.V. 
Gorpinich Mariya4Metaparameter optimization in knowledge distillationBakhteev O.Yu.Paper, Code, Slides
Vyacheslav Gorchakov4Importance Sampling Approach to Chance-Constrained DC Optimal Power FlowMaximov Y.V.Paper, Code
Konstantin Yakovlev4Selection of concordant architectures with complexity controlBakhteev O.Y.Code, Slides
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+ + diff --git a/materials/paper_guidelines/index.html b/materials/paper_guidelines/index.html new file mode 100644 index 00000000..071646c6 --- /dev/null +++ b/materials/paper_guidelines/index.html @@ -0,0 +1,262 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Papers and theses writing guidelines + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Standards

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Guidelines

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Where to sumbit

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+ + diff --git a/materials/scholarship/index.html b/materials/scholarship/index.html new file mode 100644 index 00000000..b0cf8bfc --- /dev/null +++ b/materials/scholarship/index.html @@ -0,0 +1,240 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Scholarships + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Scholarship Info

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Related information here.

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+ + diff --git a/materials/seminars/index.html b/materials/seminars/index.html new file mode 100644 index 00000000..9d60c58c --- /dev/null +++ b/materials/seminars/index.html @@ -0,0 +1,432 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Scientific seminars + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Meetings and seminars

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Meetinig with Nikita Zhivotovskiy, alumnus of the MIPT Department of Intelligent Systems, 2013

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Date: 21.04.2022

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Guest: Nikita Zhivotovskiy is a candidate of physical and mathematical sciences. He is a researcher at Google Research, Zürich.

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Meeting with Kirill Pavlov, alumnus of the MIPT Department of Intelligent Systems, 2012

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Date: 27.03.2022

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Guest: Kirill Pavlov is an alumnus, 2012, researcher.

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Meeting with Roman Sologub, alumnus of the MIPT Department of Intelligent Systems, 2010

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Date: 11.03.2022

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Guest: Roman Sologub

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Roman Sologub is a candidate of physical and mathematical sciences. He is a financial analyst from London.

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Meeting with alumni of the MIPT Department of Intelligent Systems, 2013

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Date: 17.02.2022

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Guests: Mikhail Kuznetsov, Nikita Ivkin

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The alumni of the department are engaged in research in the field of machine learning and data analysis in large commercial companies.

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Prior Distribution of Parameters in Deep Learning Model Selection Problem

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Date: 24.01.2022

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Speaker: Andrey Grabovoy

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The seminar is devoted to deep learning model distillation. We discuss the alignment of the structures of teacher and student models. Bayesian inference is used to optimize student parameters. We give an examples of distillation fully connected and recurrent neural networks as models of a teacher and a student.

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Dimension Reduction in Signal Decoding Problems

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Date: 13.12.2021

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Speaker: Roman Isachenko

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The seminar is devoted to the problem of reducing the dimension of space when solving the problem of signal decoding. The decoding process consists in restoring the relationship between two heterogeneous datasets. A feature of the problem is the presence of hidden dependencies not only in the source signals, but also in the target ones. We propose dimension reduction methods that allow using dependencies in the source and target spaces.

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Uncertainty, Out-of-distribution detection for NNs

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Date: 8.07.2021

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Speaker: Maxim Panov

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Maxim Panov (Associate Professor at Skoltech) will tell at the seminar what Uncertainty is in Bayesian inference.

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PhD defences

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Roman Isachenko, 2021

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Link to thesis

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Oleg Bakhteev, 2020

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Link to thesis

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Anastasia Motrenko, 2019

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Link to thesis

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Alexander Aduenko, 2017

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Link to thesis

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Arsentiy Kuzmin, 2017

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Link to thesis

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Master’s and Bachelor’s defences

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Bachelor’s defences, 2022

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Students: Konstantin Yakovlev, Maria Gorpinich, Antonina Kurdyukova, Vyacheslav Gorсhakov, Anton Pilkevich, Maxim Khristolybov

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Master’s defences, 2022

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Students: Petr Mokrov, Natalia Varenik, Alexey Grigoriev, Sviatoslav Panchenko, Pavel Severilov, Denis Tikhonov, Alexander Kolesov, Alexey Grishanov

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Bachelor’s defences, 2021

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Students: Drmitriy Kovalev, Anton Bishuk, Kirill Vayser, Olga Grebenkova, Ruslan Gunaev, Vladimir Zholobov, Rustem Islamov, Victor Pankratov, Nikolay Saveliev, Andrey Filatov, Anastasia Filippova, Aleksandra Khar, Vyacheslav Shokorov, Tagir Sattarov

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Master’s defences, 2021

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Students: Egor Gladin, Andrey Grabovoy, Vadim Kislinskiy, Evgeniy Kozlinskiy, Grigory Malinovsky, Egor Shulgin, Vasiliy Novitskiy, Anna Rogozina, Nikita Pletnev, Alina Samokhina, Tamaz Gadaev, Gleb Morgachev

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+ + diff --git a/materials/thesis/index.html b/materials/thesis/index.html new file mode 100644 index 00000000..00bc4ec3 --- /dev/null +++ b/materials/thesis/index.html @@ -0,0 +1,785 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Theses + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Intelligent Systems Phystech +
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+ + Machine Learning
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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2024

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Master’s Theses

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StudentThesis topicScientific adviserLink to ProjectLink to PaperLink to Slides
Maria KovalevaAddition of external information for enhancement of local embeddings for event sequences data modelsZaytsev A. A.ProjectThesisSlides
Alexander TolmachevInformation Bottleneck Analysis of Deep Neural NetworksAlexey FrolovProjectThesisSlides
Emil AlkinExpressive Power of Tensor-Train Networks With Equal TT-coresIvan OseledetsProjectThesisSlides
Klypa RomanGenerative modeling for protein structuresGrudinin S.V.ProjectThesisSlides
Ksenofontov GregoryAdversarial Schrödinger bridges on domain translation problemIsachenko R.V.ProjectPaperSlides
Barabanshchikova PolinaTverberg type theoremsPolyanskii A.A.ProjectPaperSlides
Yakovlev KonstantinGeneralized Greedy Gradient-Based Hyperparameter OptimizationBakhteev O.Y.ProjectPaperSlides
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Bachelor’s Theses

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StudentThesis topicScientific adviserLink to ProjectLink to PaperLink to Slides
Nikita KiselevBayesian Sample Size EstimationGrabovoy A.V.ProjectThesisSlides
Daniil DorinSpatial-temporal characteristics in the time series decodingGrabovoy A.V.ProjectThesisSlides
Andrey VeprikovMathematical model of the hidden feedback loop effect in machine learning systemsKhritankov A.S.ProjectThesisSlides
Maria NikitinaAnalysis of distribution bias in contrastive learningIsachenko R.V.ProjectThesisSlides
Anastasia VoznyukDetection of machine-generated fragments based on text style change analysisGrabovoy A. V.ProjectThesisSlides
Anna RemizovaReducing the dimension of the space of the trainable parameters in the domain adaptation problemGrabovoy A. V.ProjectThesisSlides
Okhotnikov NikitaInterconnected latent representations for outfit generation taskIsachenko R.V.ProjectThesisSlides
Terentyev AlexanderClassification of trajectories of dynamic systems using physically-informed neural networksIsachenko R.V.ProjectThesisSlides
Ignashin IgorBayesian distillation of transformer-based modelsGrabovoy A. V.ProjectThesisSlides
Ilgam LatypovAn effective method of scalarization and search for a competitive solution without iterative calculations for Lipschitz functionsDorn Y.V.ProjectThesisSlides
Kirill SemkinTensor decomposition and forecast for multidimensional time seriesIsachenko R.V.ProjectThesisSlides
Matvei KreininOn methods with preconditioning and weight decayingBeznosikov A.N.ProjectThesisSlides
Petr BabkinDifferentiable algorithm for searching ensembles of deep learning models with diversity controlBakhteev O.Y.ProjectThesisSlides
Bogdanov AlexanderGradient approximations using a zero-order oracle and memorization techniqueBeznosikov A.N.ProjectThesisSlides
Oleinik MikhailKnowledge distillation in deep neural networks using model structure alignment methodsBakhteev O.Y.ProjectThesisSlides
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2023

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PhD’s Theses

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| Student | Thesis topic | Scientific adviser | Link to Project | Link to Paper | Link to Slides | +|:—:|:—:|:—:|:—:|:—:|:—:|

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Master’s Theses

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StudentThesis topicScientific adviserLink to ProjectLink to PaperLink to Slides
Rustem IslamovDistributed Newton-Type Methods with Communication Compression and Bernoulli AggregationStrijov V.V., Richtarik P.ProjectPaperSlides
Olga GrebenkovaAutomatic detection of focal cortical dysplasia for sparse data representationBurnaev E.V.ProjectThesisSlides
Anton BishukControlled Graph GenerationZukhba A.V.ProjectThesisSlides
Nadezhda AlsahanovaSelection of tensor representations for multiview forecastingStrijov V.V.ProjectThesisSlides
Robert SafiullinMultimodel representation of dynamic systemsStrijov V.V.ProjectThesisSlides
Shokorov ViacheslavDeep ensemble boostingVetrov D.P.ProjectThesisSlides
Filatov AndreiText Interfaces for Event SequencesStrijov V.V.ProjectThesisSlides
Viktor PankratovProbabilistic Topic Modeling for Unbalanced Text CollectionsVorontsov K.V.ProjectThesisSlides
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Bachelor’s Theses

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StudentThesis topicScientific adviserLink to ProjectLink to PaperLink to Slides
Eduard VladimirovState space models in ECoG signal classification problemStrijov V.V.ProjectPaperSlides
Georgiy ZharovSearching for links between fragments of manipulations with named entities in textsVorontsov K.V.ProjectPaperSlides
Alexander MolozhavenkoRiemannian optimization on the manifold of fixed rank tensor trains with the orthogonality conditionGasnikov A.V.ProjectPaperSlides
Ivan LukyanenkoManipulation detection in newsVorontsov. K.V.ProjectPaperSlides
Antyshev TikhonGradient Sliding for Composite Saddle Point ProblemsGasnikov A.V.ProjectPaperSlides
Kornilov NikitaGradient Free Methods for Non-Smooth Convex Stochastic Optimization with Heavy Tails on Convex CompactGasnikov A.V.ProjectPaperSlides
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2022

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PhD’s Theses

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StudentThesis topicScientific adviserLink to ProjectLink to PaperLink to Slides
Andrey GrabovoyBayesian DistilationStrijov V.V.ProjectThesisSlides
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Master’s Theses

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentThesis topicScientific adviserLink to ProjectLink to PaperLink to Slides
Alexey GrigorevRegularization of neural layer via construction of frame in parameter spaceGneushev A.N.ProjectThesisSlides
Natalia VarenikBuilding a connectivity map of functional groups in the problem of decoding brain signalsStrijov V.V.ProjectThesisSlides
Pavel SeverilovChoosing the optimal model in the problem of modeling dynamics of a physical system by neural networksStrijov V.V.ProjectThesisSlides
Panchenko SviatoslavBilinearity of geometric product for the task of signal decodingStrijov V.V.ProjectThesisSlides
Alexey GrishanovApplication of Reinforcement Learning for recommendation system personalizationVorontsov K.V.ProjectThesisSlides
Petr MokrovWasserstein gradient flows: modeling and applicationsBurnaev E.V.ProjectThesisSlides
Tikhonov DenisForecasting models selection for quasi-periodic time seriesStrijov V.V.ProjectThesisSlides
Kolesov AlexanderAdversarial training approach for a neural network in Transfer Learning problemBahteev O.Y.ProjectThesisSlides
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Bachelor’s Theses

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StudentThesis topicScientific adviserLink to ProjectLink to PaperLink to Slides
Kurdyukova AntoninaDimensionality reduction in the phase space in canonical correlation analysisStrijov V.V.ProjectThesisSlides
Gorpinich MariyaMetaparameter optimization in knowledge distillationBakhteev O.Yu.ProjectThesisSlides
Gorсhakov VyacheslavImportance Sampling Approach to Chance-Constrained DC Optimal Power FlowMaximov Y.V.ProjectThesisSlides
Pilkevich AntonOptimization of the criterion given by the neural network model in the text detoxification taskStrijov V.V.ProjectThesisSlides
Khristolybov MaximModel parameter space for phase trajectory approximationStrijov V.V.ProjectThesisSlides
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+ + diff --git a/people/aduenko_aa/index.html b/people/aduenko_aa/index.html new file mode 100644 index 00000000..8accd903 --- /dev/null +++ b/people/aduenko_aa/index.html @@ -0,0 +1,406 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Aleksander Aduenko + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Aleksander Aduenko

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He graduated with honors from MIPT in 2015. He defended his Ph.D. dissertation on mutlimodel selection for classification problems in 2017, candidate of physical and mathematical sciences. +He is an author of more than 15 scientific papers on Bayesian inference and data analysis.

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Teaches:

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+ + diff --git a/people/apishev_ma/index.html b/people/apishev_ma/index.html new file mode 100644 index 00000000..f33be8e6 --- /dev/null +++ b/people/apishev_ma/index.html @@ -0,0 +1,272 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Murat Apishev + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Intelligent Systems Phystech +
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Murat Apishev

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He graduated with honors from MSU in 2017. He defended his Ph.D. dissertation on methods of effective implementation of topic modeling with additive regularization in 2020, candidate of technical sciences. +He is an author of more than 8 scientific papers on topic modeling. He is one of the authors of open-source topic modeling library bigartm.

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Professional interests: topic modeling, parallel algorithms for topic modeling, semantic text representation.

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+ + diff --git a/people/bakhteev_oy/index.html b/people/bakhteev_oy/index.html new file mode 100644 index 00000000..198d1fae --- /dev/null +++ b/people/bakhteev_oy/index.html @@ -0,0 +1,440 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Oleg Bakhteev + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Oleg Bakhteev

+
+ + + + + + + Personal Website
+ + + + bakhteev(at)phystech.edu
+ + + + google scholar
+ + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

He graduated with honors from MIPT in 2016. He defended his Ph.D. dissertation on methods of deep learning model selection in 2020, candidate of physical and mathematical sciences. +He is an author of more than 29 scientific papers on model selection and natural language processing.

+ +

Professional interests: model selection, deep learning, neural networks, Bayesian inference, natural language processing.

+ +

Main publications

+
    +
  1. Yakovel K., Grebenkova O., Bakhteev O., Strijov V. Neural architecture search with structure complexity control (2021). Proceedings of the 10th International Conference on Analysis of Images, Social Networks and Texts.
    2. +
  2. Bakhteev, O. Y., & Strijov, V. V. (2020). Comprehensive analysis of gradient-based hyperparameter optimization algorithms. Annals of Operations Research, 289(1), 51-65.
    3. +
  3. Bakhteev, O. Y., & Strijov, V. V. (2018). Deep learning model selection of suboptimal complexity. Automation and remote control, 79(8), 1474-1488.
    4. +
+ +

Full list of publications

+ +

Conferences and workshops

+
    +
  1. Bakhteev O., Ogaltsov A., Khazov A., Safin K., Kuznetsova R. CrossLang: The System of Cross-lingual Plagiarism Detection. NeurIPS, Workshop on Systems for ML. 2019.
    2. +
  2. Kuznetosva R., Bakhteev O. Variational Bi-domain Triplet Autoencoder. NeurIPS, Visually Grounded Interaction and Language workshop. 2018.
    3. +
  3. Bakhteev O., Khazov A. Author Masking using Sequence-to-Sequence Models. CLEF. 2017.
    4. +
+ +

Full list of talks at conferences and workshops

+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/beznosikov_an/index.html b/people/beznosikov_an/index.html new file mode 100644 index 00000000..1a078263 --- /dev/null +++ b/people/beznosikov_an/index.html @@ -0,0 +1,415 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Aleksandr Beznosikov + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Aleksandr Beznosikov

+
+ + + + + + + + + + + + + + +  +
+  + + + + +

Short bio.

+ +

He graduated from MIPT in TODO. He defended his Ph.D. dissertation on in TODO, candidate of physical and mathematical sciences. +He is an author of more than TODO scientific papers on .

+ +

Professional interests: TODO.

+ +

Publications

+
    +
  1. TODO
    2. +
  2. TODO
    3. +
+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/bishuk_ay/index.html b/people/bishuk_ay/index.html new file mode 100644 index 00000000..2e98d67b --- /dev/null +++ b/people/bishuk_ay/index.html @@ -0,0 +1,407 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Anton Bishuk + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Anton Bishuk

+
+ + + + + + + + + anton.bishuk@mail.ru
+ + + + + + + +  +
+  + + + + +

Anton graduated from MIPT in 2021. He is a master student of the Department of Intelligent Systems.

+ +

Professional interests: Active learning, machine learning graph models, generative models.

+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/chekhovich_yv/index.html b/people/chekhovich_yv/index.html new file mode 100644 index 00000000..606b1be8 --- /dev/null +++ b/people/chekhovich_yv/index.html @@ -0,0 +1,276 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Yury Chekhovich + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+
    +
+
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Yury Chekhovich

+
+ + + + + + + Personal Website
+ + + + + + google scholar
+ + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

He graduated from MIPT in 1999. He defended his Ph.D. dissertation on the algebraic theory of synthesis of algorithms of trend extraction in 2004, candidate of physical and mathematical sciences. +He is the author of more than 93 scientific papers on data analysis. Under his supervision, 3 candidate theses were defended.

+ +

Professional interests: classification approach for synthesis and identification of simulational models of complex social-technical systems, transport models, algorithms, and models of text reuse.

+ + + + + + + + + + +
+ + +
+ + diff --git a/people/dulin_sk/index.html b/people/dulin_sk/index.html new file mode 100644 index 00000000..6a7e5efc --- /dev/null +++ b/people/dulin_sk/index.html @@ -0,0 +1,275 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Sergey Dulin + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+
    +
+
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Sergey Dulin

+
+ + + + + + + Personal Website
+ + + + + + + + Scopus
+ + + eLibrary
+ + + Math-Net
+ +  +
+  + + + + +

Doctor of Technical Sciences, Full Professor, Academician of the Russian Academy of Natural Sciences. Author of more than 95 scientific papers.

+ +

Professional interests: knowledge representation in artificial intelligence systems.

+ + + + + + + + + + +
+ + +
+ + diff --git a/people/filatov_av/index.html b/people/filatov_av/index.html new file mode 100644 index 00000000..79e356ea --- /dev/null +++ b/people/filatov_av/index.html @@ -0,0 +1,410 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Andrey Filatov + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Andrey Filatov

+
+ + + + + + + + + filatovandreiv@gmail.com
+ + + + google scholar
+ + + + + +  +
+  + + + + +

Andrei is graduated with honours from MIPT in 2021. Currently, he is a MSc student of the Department of Intelligent Systems. +Additionally, he is doing internship in EPFL VILAB under the supervision of Amir Zamir in the field of computer vision.

+ +

Professional interests: Computer Vision, Multi-task learning, Multi-modal learning

+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/gneushev_an/index.html b/people/gneushev_an/index.html new file mode 100644 index 00000000..31f3aed1 --- /dev/null +++ b/people/gneushev_an/index.html @@ -0,0 +1,276 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Alexander Gneushev + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+
    +
+
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Alexander Gneushev

+
+ + + + + + + Personal Website
+ + + + + + google scholar
+ + + + + eLibrary
+ + + Math-Net
+ +  +
+  + + + + +

He is a candidate of physical and mathematical sciences. +He is an author of more than 25 scientific papers on data analysis.

+ +

Professional interests: image processing and analysis, pattern recognition, biometric identification, neural network models for image analysis, development of models and methods for feature extraction for the tasks of detecting and classifying objects in images, face recognition, detection of a pedestrian in an image, super resolution and restoration of images, modeling methods and regularization in training convolutional neural networks for image analysis, biometric identification by the iris of the eye, selection and tracking of face elements in the image, road scene analysis, vehicle speed estimation, vehicle type classification

+ + + + + + + + + + +
+ + +
+ + diff --git a/people/grabovoy_av/index.html b/people/grabovoy_av/index.html new file mode 100644 index 00000000..1607d505 --- /dev/null +++ b/people/grabovoy_av/index.html @@ -0,0 +1,440 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Andrey Grabovoy + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Andrey Grabovoy

+
+ + + + + + + Personal Website
+ + + + grabovoy.av@phystech.edu
+ + + + google scholar
+ + + OrcID
+ + + Scopus
+ + + + Math-Net
+ +  +
+  + + + + +

He graduated with honors from MIPT in 2021. Since 2021 he is a postgraduate student of the Department of Intelligent Systems. +He is an author of more than 14 scientific papers on knowledge distillation, model selection, natural language processing.

+ +

Publications

+
    +
  1. Грабовой А.В., Стрижов В.В. Байесовская дистилляция моделей глубокого обучения // Автоматика и телемеханика, 2021.
    2. +
  2. Грабовой А.В., Стрижов В.В. Анализ выбора априорного распределениядля смеси экспертов // Журнал вычислительной математики и матема-тической физики, 2021.
    3. +
  3. A. Grabovoy, V. Strijov. Quasi-periodic time series clustering for human //Lobachevskii Journal of Mathematics, 2020.
    4. +
  4. Грабовой А.В., Бахтеев О. Ю., Стрижов В.В. Введение отношения порядка на множестве параметров аппроксимирующих моделей // Инфор-матика и ее применения, 2020.
    5. +
  5. Грабовой А.В., Бахтеев О.Ю., Стрижов В.В. Определение релевантности параметров нейросети // Информатика и ее применения, 2019.
    6. +
  6. Грабовой А.В., Стрижов В.В. Вероятностная интерпретация задачи дистилляции // Автоматика и телемеханика, 2022.
    7. +
  7. A. Grabovoy, T. Gadaev, A. Motrenko, V. Strijov Numerical methods ofminimum sufficient sample size estimation for linear models // LobachevskiiJournal of Mathematics, 2023.
    8. +
  8. A. Bazarova, A. Grabovoy , V. Strijov Analysis of the properties ofprobabilistic models in learning problems with an expert // Journal ofComputational Mathematics, 2023.
    9. +
+ +

Conferences

+
    +
  1. Задача обучения с экспертом для построения интерпретируемых моделей машинного обучения, Международная конференция «Интеллектуализация обработки информации», 2020.
    2. +
  2. Привилегированная информация и дистилляция моделей, Всероссийская конференция «63-я научная конференция МФТИ», 2020.
    3. +
  3. Введение отношения порядка на множестве параметров нейронной сети, Всероссийская конференция «Математические методы распознавания об-разов ММРО», 2019.
    4. +
  4. Анализ априорных распределений в задаче смеси экспертов, Всероссийская конференция «62-я научная конференция МФТИ», 2019.
    5. +
  5. Поиск оптимальной модели при помощи алгоритмов прореживания, Всероссийская конференция «61-я научная конференция МФТИ», 2018.
    6. +
  6. Автоматическое определение релевантности параметров нейросети, Международная конференция «Интеллектуализация обработки информации», 2018
    7. +
+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/grebenkova_os/index.html b/people/grebenkova_os/index.html new file mode 100644 index 00000000..46342491 --- /dev/null +++ b/people/grebenkova_os/index.html @@ -0,0 +1,414 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Olga Grebenkova + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Olga Grebenkova

+
+ + + + + + + + + grebenkova.os@phystech.edu
+ + + + + + + +  +
+  + + + + +

Olga graduated from MIPT in 2021. She is a master student of the Department of Intelligent Systems. +She is an author of a few scientific papers on machine learning.

+ +

Professional interests: Generative models, Neural Architechture Search

+ +

Selected papers

+ + + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/grishanov_av/index.html b/people/grishanov_av/index.html new file mode 100644 index 00000000..a678f585 --- /dev/null +++ b/people/grishanov_av/index.html @@ -0,0 +1,419 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Alexey Grishanov + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Alexey Grishanov

+
+ + + + + + + + + grishanov.av@phystech.edu
+ + + + google scholar
+ + + OrcID
+ + + + +  +
+  + + + + +

I am a Phd student at Moscow Institute of Physics and Tecnhology (MIPT) and member of Sber AI Lab.

+ +

Professional interests: Recommender systems, Reinforcement Learning.

+ +

Publications

+ +
    +
  1. Grishanov A., Ianina A., Vorontsov K. Multiobjective Evaluation of Reinforcement Learning Based Recommender Systems // Proceedings of the 16th ACM Conference on Recommender Systems (RecSys ’22). Pp. 622–627.
    2. +
  2. Artemiev A.*, Parinov D.*, Grishanov A.*, Borisov I., Vasilev A., Muravetskii D., Rezvykh A., Goncharov A., and Savchenko A. Leveraging Summarization for Unsupervised Dialogue Topic Segmentation // Findings of the NAACL 2024.
    3. +
+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/index.html b/people/index.html new file mode 100644 index 00000000..24682efa --- /dev/null +++ b/people/index.html @@ -0,0 +1,877 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Lecturers + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Founders of the Department

+
+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Konstantin Rudakov +

+
+ + + + + + + + + + + + + + + + + +
+

+ + + + Konstantin Vorontsov +

+
+ + + + + +
+

+ + + + Yuri Zhuravlyov +

+
+ + +
+ +
+

Doctors of Science

+
+
+ +
+ + + + + + + + + + + + + + +
+

+ + + + Sergey Dulin +

+
+ + + + + + + + + + + + + + + +
+

+ + + + Vladimir Khoroshevsky +

+
+ + + + + + + + + +
+

+ + + + Ivan Matveev +

+
+ + + +
+

+ + + + Leonid Mestetskiy +

+
+ + + + + +
+

+ + + + Elena Mohonko +

+
+ + + + + + + + + + + + + + + +
+

+ + + + Vadim Strijov +

+
+ + + + + + + +
+

+ + + + Vladimir Tsurkov +

+
+ + + + + +
+

+ + + + Konstantin Vorontsov +

+
+ + + + + + +
+ +
+

PhD

+
+
+ +
+ + +
+

+ + + + Aleksander Aduenko +

+
+ + + +
+

+ + + + Murat Apishev +

+
+ + + +
+

+ + + + Oleg Bakhteev +

+
+ + + +
+

+ + + + Aleksandr Beznosikov +

+
+ + + + + +
+

+ + + + Yury Chekhovich +

+
+ + + + + + + +
+

+ + + + Alexander Gneushev +

+
+ + + +
+

+ + + + Andrey Grabovoy +

+
+ + + + + + + +
+

+ + + + Roman Isachenko +

+
+ + + + + + + +
+

+ + + + Anton Khritankov +

+
+ + + +
+

+ + + + Dmitriy Kropotov +

+
+ + + + + + + +
+

+ + + + Archil Meysuradze +

+
+ + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Ivan Torshin +

+
+ + + + + + + + + + + + +
+ +
+

Graduate Students

+
+
+ +
+ + + + + + + + + + +
+

+ + + + Anton Bishuk +

+
+ + + + + + + +
+

+ + + + Andrey Filatov +

+
+ + + + + + + +
+

+ + + + Olga Grebenkova +

+
+ + + +
+

+ + + + Alexey Grishanov +

+
+ + + + + + + +
+

+ + + + Kirill Khrylchenko +

+
+ + + + + + + + + + + + + + + +
+

+ + + + Petr Mokrov +

+
+ + + +
+

+ + + + Artem Popov +

+
+ + + +
+

+ + + + Mark Potanin +

+
+ + + + + +
+

+ + + + Alina Samokhina +

+
+ + + +
+

+ + + + Pavel Severilov +

+
+ + + + + +
+

+ + + + Denis Tikhonov +

+
+ + + + + + + +
+

+ + + + Anna Volodkevich +

+
+ + + + + +
+

+ + + + Konstantin Yakovlev +

+
+ + + + +
+ + + + +
+ + +
+ + diff --git a/people/isachenko_rv/index.html b/people/isachenko_rv/index.html new file mode 100644 index 00000000..21214414 --- /dev/null +++ b/people/isachenko_rv/index.html @@ -0,0 +1,420 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Roman Isachenko + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Roman Isachenko

+
+ + + + + + + + + roman.isachenko(at)phystech.edu
+ + + + google scholar
+ + + + Scopus
+ + + +  +
+  + + + + +

He graduated from MIPT in 2018. He defended his Ph.D. dissertation on dimension reduction for signal decoding tasks in 2021, candidate of physical and mathematical sciences. +He is an author of more than 6 scientific papers on data analysis and signal processing.

+ +

Professional interests: generative modelling, deep learning, signal processing.

+ +

Main publications

+
    +
  1. Isachenko R., Yaushev F., Strijov V. (2021). Concordant models for latent space projections in forecasting. Systems and Means of Informatics, 31(1), 4–16.
    2. +
  2. Isachenko R., Strijov V. (2018). Quadratic Programming Optimization with Feature Selection for Nonlinear Models. Lobachevskii Journal of Mathematics, 39(9), 1179–1187.
    3. +
  3. Isachenko R., Zharikov I., Bochkarev A., Strijov V. (2018). Feature Generation for Physical Activity Classification. Artificial Intelligence and Decision Making, 3: 20–27, 2018.
    4. +
+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/khoroshevsky_vf/index.html b/people/khoroshevsky_vf/index.html new file mode 100644 index 00000000..06034964 --- /dev/null +++ b/people/khoroshevsky_vf/index.html @@ -0,0 +1,269 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Vladimir Khoroshevsky + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+
    +
+
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Vladimir Khoroshevsky

+
+ + + + + + + + + + + google scholar
+ + + + + eLibrary
+ + +  +
+  + + + + +

Associate Professor, Doctor of Technical Sciences. Author of more than 60 scientific papers.

+ + + + + + + + + + +
+ + +
+ + diff --git a/people/khrilchenko_ky/index.html b/people/khrilchenko_ky/index.html new file mode 100644 index 00000000..94315333 --- /dev/null +++ b/people/khrilchenko_ky/index.html @@ -0,0 +1,267 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Kirill Khrylchenko + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+
    +
+
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Kirill Khrylchenko

+
+ + + + + + + + + + + + + + +  +
+  + + + + +

He graduated with honors from MSU in 2020.

+ +

Professional interests: natural language processing, topic modeling, deep learning, applied data analysis problems.

+ + + + + + + + + + +
+ + +
+ + diff --git a/people/khritankov_as/index.html b/people/khritankov_as/index.html new file mode 100644 index 00000000..999aea64 --- /dev/null +++ b/people/khritankov_as/index.html @@ -0,0 +1,412 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Anton Khritankov + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Anton Khritankov

+
+ + + + + + + + + + + google scholar
+ + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

He graduated with honors from MIPT in 2007. He defended his Ph.D. dissertation on methods for assessing the performance of distributed systems in 2010, candidate of physical and mathematical sciences. +He is an author of more than 24 scientific papers on performance evaluation, software engineering methods and systems analysis.

+ +

Professional interests: Software systems architecture and design, software development methodologies and processes, distributed computing and performance evaluation.

+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/kropotov_da/index.html b/people/kropotov_da/index.html new file mode 100644 index 00000000..2c73b663 --- /dev/null +++ b/people/kropotov_da/index.html @@ -0,0 +1,410 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Dmitriy Kropotov + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Dmitriy Kropotov

+
+ + + + + + + + + + + google scholar
+ + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

He graduated from MSU in 2003. +He is an author of more than 90 scientific papers on mathematical methods of machine learning and data analysis.

+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/matveev_ia/index.html b/people/matveev_ia/index.html new file mode 100644 index 00000000..24c59601 --- /dev/null +++ b/people/matveev_ia/index.html @@ -0,0 +1,274 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Ivan Matveev + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+
    +
+
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Ivan Matveev

+
+ + + + + + + + + + + google scholar
+ + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

He graduated from MIPT in 1997. He defended his Ph.D. dissertation on models of object recognition in real-time systems of computer stereovision in 1999. He defended his Doctor of Science dissertation in 2014 on metohds and algorithms of automatic iris image processing. He is a Doctor technical sciences. +He is an author of more than 95 scientific papers on pattern recognition and image processing.

+ +

Professional interests: image processing, pattern recognition, biometric identification.

+ + + + + + + + + + +
+ + +
+ + diff --git a/people/mestetskiy_lm/index.html b/people/mestetskiy_lm/index.html new file mode 100644 index 00000000..5214a52f --- /dev/null +++ b/people/mestetskiy_lm/index.html @@ -0,0 +1,414 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Leonid Mestetskiy + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Leonid Mestetskiy

+
+ + + + + + + Personal Website
+ + + + + + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

He graduated from MSU in 1971. He is a Doctor of Technical Sciences (1992), full professor (1998), full member of the Russian Academy of Natural Sciences (2004). +He is the author of more than 150 on applied mathematics, modeling, computer graphics, image processing and pattern recognition. Under his supervision, 14 candidate theses were defended.

+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/meysuradze_ai/index.html b/people/meysuradze_ai/index.html new file mode 100644 index 00000000..34131e20 --- /dev/null +++ b/people/meysuradze_ai/index.html @@ -0,0 +1,408 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Archil Meysuradze + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Archil Meysuradze

+
+ + + + + + + + + + + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

He graduated from MIPT in 1999. He defended his Ph.D. dissertation 2006, candidate of physical and mathematical sciences. +He is an author of more than 51 scientific papers.

+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/mohonko_ez/index.html b/people/mohonko_ez/index.html new file mode 100644 index 00000000..b78a27f2 --- /dev/null +++ b/people/mohonko_ez/index.html @@ -0,0 +1,268 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Elena Mohonko + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+
    +
+
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Elena Mohonko

+
+ + + + + + + + + + + + + + eLibrary
+ + +  +
+  + + + + +

She is a Doctor of physical and mathematical sciences. +She is an author of more than 34 scientific papers.

+ + + + + + + + + + +
+ + +
+ + diff --git a/people/mokrov_pv/index.html b/people/mokrov_pv/index.html new file mode 100644 index 00000000..7973667c --- /dev/null +++ b/people/mokrov_pv/index.html @@ -0,0 +1,420 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Petr Mokrov + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Petr Mokrov

+
+ + + + + + + Personal Website
+ + + + mokrov.pv@phystech.edu
+ + + + google scholar
+ + + + + +  +
+  + + + + +

He graduated with a master’s degree from the joint program of MIPT (department of Intellectual systems) and Skoltech (Data Science) in 2022. He is a PhD student at Skoltech under the supervision of Evgeny Burnaev. He is an author of a few scientific papers on machine learning.

+ +

Professional interests: generative modeling, optimal transport

+ +

Publications

+
    +
  1. Large-scale Wasserstein Gradient Flows, NeurIPS’2021
    2. +
  2. Building the Bridge of Schrödinger: A Continuous Entropic Optimal Transport Benchmark, NeurIPS’2023
    3. +
  3. Energy-guided Entropic Neural Optimal Transport, ICLR’2024
    4. +
  4. Neural Optimal Transport with General Cost Functionals, ICLR’2024
    5. +
+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/popov_as/index.html b/people/popov_as/index.html new file mode 100644 index 00000000..a5164702 --- /dev/null +++ b/people/popov_as/index.html @@ -0,0 +1,409 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Artem Popov + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Artem Popov

+
+ + + + + + + Personal Website
+ + + + + + google scholar
+ + + + + +  +
+  + + + + +

He graduated with honors from MSU in 2019. He is an author of more than 4 scientific papers on natural language processing and data analysis.

+ +

Professional interests: word embedding models, natural language processing, distributional semantics, topic modeling.

+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/potanin_ms/index.html b/people/potanin_ms/index.html new file mode 100644 index 00000000..4de95ba4 --- /dev/null +++ b/people/potanin_ms/index.html @@ -0,0 +1,406 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Mark Potanin + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Mark Potanin

+
+ + + + + + + + + + + google scholar
+ + + + + +  +
+  + + + + +

He graduated from MIPT. Since 2019 he is a postgraduate student of the Department of Intelligent Systems. +He is an author of more than 5 scientific papers on machine learning.

+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/rudakov_kv/index.html b/people/rudakov_kv/index.html new file mode 100644 index 00000000..89395032 --- /dev/null +++ b/people/rudakov_kv/index.html @@ -0,0 +1,4 @@ + + + + \ No newline at end of file diff --git a/people/samokhina_am/index.html b/people/samokhina_am/index.html new file mode 100644 index 00000000..a344fc2a --- /dev/null +++ b/people/samokhina_am/index.html @@ -0,0 +1,426 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Alina Samokhina + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Alina Samokhina

+
+ + + + + + + Personal Website
+ + + + alina.samokhina@phystech.edu
+ + + + google scholar
+ + + + + +  +
+  + + + + +

She graduated from MIPT in 2021. Since 2021 she is a postgraduate student of the Department of Intelligent Systems. +She is an author of some scientific papers on machine learning and neuroscience.

+ +

Professional interests: brain-computer interfaces, continuous models.

+ +

Publications

+
    +
  1. А. М. Самохина, Р. Г. Нейчев, В. В. Гончаренко, Р. К. Григорян, В. В. Стрижов Модели классификации выборки вызванных потенциалов P300 // Системы и средства информатики, 2022
    2. +
  2. Matvey Bulat, Alexandra Karpman, Alina Samokhina, Alexander Panov Playing a P300-based BCI VR game leads to changes in cognitive functions of healthy adults // BioRxiv, 2020
    3. +
+ +

Conferences

+
    +
  1. Подходы к мультиклассовой классификации датасета потенциалов P300, Международная конференция «Интеллектуализация обработки информации», 2020.
    2. +
  2. Датасет потенциалов P300 и подходы к его обработке, Всероссийская конференция «63-я научная конференция МФТИ», 2020.
    3. +
+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/severilov_pa/index.html b/people/severilov_pa/index.html new file mode 100644 index 00000000..c171bafb --- /dev/null +++ b/people/severilov_pa/index.html @@ -0,0 +1,277 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Pavel Severilov + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+
    +
+
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Pavel Severilov

+
+ + + + + + + + + severilov.pa@phystech.edu
+ + + + + + + +  +
+  + + + + +

He graduated from Moscow Institute of Physics and Tecnhology (MIPT) in 2022. Since 2022 he is a postgraduate student of the Department of Intelligent Systems.

+ +

He is an author of DL in audio course and couple of papers on deep learning in signals.

+ +

Professional interests: NLP, Audio, Signals (EEG/MEG/fMRI)

+ +

Selected papers

+ + + + + + + + + + + +
+ + +
+ + diff --git a/people/strijov_vv/index.html b/people/strijov_vv/index.html new file mode 100644 index 00000000..f8a0fea7 --- /dev/null +++ b/people/strijov_vv/index.html @@ -0,0 +1,446 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Vadim Strijov + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Vadim Strijov

+
+ + + + + + + Personal Website
+ + + + strijov@ccas.ru
+ + + + google scholar
+ + + OrcID
+ + + Scopus
+ + + eLibrary
+ + + Math-Net
+ +  +
+  + + + + +

Vadim Strijov is a professor at the Moscow Institute of Physics and Technology, head of the Department of Intelligent Systems MIPT. He is graduated from the Ufa State Aviation Technical University in 1992. In 2002 he obtained PhD from the Computer Center of the Russian Academy of Sciences with his thesis on Expert estimations concordance. In 2014 he obtained a degree of Doctor of Sciences in Physics and Mathematics with his thesis on probabilistic model generation and multi-model selection. He is an author of more than two hundred scientific papers on machine learning and data analysis. Eight PhD theses were defended with his supervision. In 2020 he was awarded the Ilya Segalovich Prize for his significant contribution to the development of the scientific community.

+ +

Professional interests: multivariate statistics, machine learning, functional data analysis, model generation and selection, Bayesian multimodeling, spatial time series analysis, biomedical signal analysis.

+ +

Selected papers

+ + + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/tikhonov_dm/index.html b/people/tikhonov_dm/index.html new file mode 100644 index 00000000..f5d031fa --- /dev/null +++ b/people/tikhonov_dm/index.html @@ -0,0 +1,406 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Denis Tikhonov + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Denis Tikhonov

+
+ + + + + + + tihonov.dm@phystech.edu
+ + + + + + + +  +
+  + + + + +

He graduated from Moscow Institute of Physics and Tecnhology (MIPT) in 2022. +Since 2022 he is a postgraduate student of the Department of Intelligent Systems.

+ +

Professional interests: time series, dynamic, signals (EEG/MEG/fMRI)

+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/torshin_iy/index.html b/people/torshin_iy/index.html new file mode 100644 index 00000000..b025d2e7 --- /dev/null +++ b/people/torshin_iy/index.html @@ -0,0 +1,413 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Ivan Torshin + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Ivan Torshin

+
+ + + + + + + Personal Website
+ + + + + + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

He is a candidate of physical and mathematical sciences, and also a candidate of chemical sciences. +He is an author of more than 600 scientific papers on computer science, applied mathematics, biomedicine, bioinformatics, biophysics and chemistry.

+ +

Professional interests: “metric” and “binary” approaches for poorly formalized problems, generation of problem-oriented metrics and analysis of metric configurations, combinatorial theory of solvability, theory of classification of feature values, +graph theory and its combinatorial applications in chemoinformatics, data analysis of biomedical research, bioinformatics.

+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/tsurkov_vi/index.html b/people/tsurkov_vi/index.html new file mode 100644 index 00000000..160aea9d --- /dev/null +++ b/people/tsurkov_vi/index.html @@ -0,0 +1,274 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Vladimir Tsurkov + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+
    +
+
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Vladimir Tsurkov

+
+ + + + + + + Personal Website
+ + + + + + google scholar
+ + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

He graduated from MIPT in 1968. He defended his Ph.D. dissertation in 1972. He defended his Doctor of Science dissertation in 1984. He is a Doctor of Physical and Mathematical Sciences, Academician of the Russian Academy of Natural Sciences. +He is an author of more than 111 scientific papers.

+ + + + + + + + + + +
+ + +
+ + diff --git a/people/volodkevich_aa/index.html b/people/volodkevich_aa/index.html new file mode 100644 index 00000000..a587654d --- /dev/null +++ b/people/volodkevich_aa/index.html @@ -0,0 +1,402 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Anna Volodkevich + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Anna Volodkevich

+
+ + + + + + + + + + + + + + +  +
+  + + + + + + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/vorontsov_kv/index.html b/people/vorontsov_kv/index.html new file mode 100644 index 00000000..8e0c905e --- /dev/null +++ b/people/vorontsov_kv/index.html @@ -0,0 +1,418 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Konstantin Vorontsov + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Konstantin Vorontsov

+
+ + + + + + + Personal Website
+ + + + + + google scholar
+ + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

He graduated from MIPT in 1994. He defended his Ph.D. dissertation in 1999. In 2010 he defended his Doctor of Science dissertation. He is a Doctor of physical and mathematical sciences, professor of the Russian Academy of Sciences. +He is an author of more than 115 scientific papers on machine learning and data analysis. Under his supervision, 17 candidate theses were defended.

+ +

Professional interests: data science, data analysis, machine learning, pattern recognition, mathematical statistics, discrete mathematics, numerical optimization, big data, practical data analysis in different areas.

+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/yakovlev_kd/index.html b/people/yakovlev_kd/index.html new file mode 100644 index 00000000..b9191975 --- /dev/null +++ b/people/yakovlev_kd/index.html @@ -0,0 +1,406 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Konstantin Yakovlev + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Intelligent Systems Phystech +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Konstantin Yakovlev

+
+ + + + + + + + + + + + + + +  +
+  + + + + +

He graduated from Moscow Institute of Physics and Tecnhology (MIPT) in 2024. +Since 2024 he is a postgraduate student in MIPT.

+ +

Professional interests: TODO

+ + + + + + + + +   +
+

Teaches:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/people/zhuravlyov_yv/index.html b/people/zhuravlyov_yv/index.html new file mode 100644 index 00000000..bca6ca6e --- /dev/null +++ b/people/zhuravlyov_yv/index.html @@ -0,0 +1,4 @@ + + + + \ No newline at end of file diff --git a/robots.txt b/robots.txt new file mode 100644 index 00000000..5b3a5b65 --- /dev/null +++ b/robots.txt @@ -0,0 +1 @@ +Sitemap: https://intsystems.github.io/sitemap.xml diff --git a/ru/about/index.html b/ru/about/index.html new file mode 100644 index 00000000..9d125d86 --- /dev/null +++ b/ru/about/index.html @@ -0,0 +1,316 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + О кафедре + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + +

Кафедра интеллектуальных систем

+

Физтех-школа прикладной математики и информатики МФТИ

+ +

Базовая кафедра выпускает бакалавров и магистров по направлению 010900 «Прикладные математика и физика». Обучение на кафедре ведется по трем специализациям «Интеллектуальный анализ данных», «Проектирование и организация систем», «Информационный поиск и машинное обучение». Базовая организация – Вычислительный центр ФИЦ “Информатика и управление” Российской академии наук.

+ +

Базовая организация – Вычислительный центр РАН, ФИЦ «Информатика и управление» Российской академии наук. Создана академиком РАН и выдающимся российским математиком, специалистом в области математических методов распознавания, прогнозирования и интеллектуального анализа данных Константином Владимировичем Рудаковым. Кафедра активно развивается с 2003 года в рамках научной школы академика РАН Юрия Ивановича Журавлева. Существенный вклад в развитие кафедры внесли профессор РАН, д.ф.-м.н. К.В. Воронцов и д.ф.-м.н. В.В. Стрижов.

+ +

Преподаватели кафедры

+

20 исследователей: профессор РАН, доктора и кандидаты наук. Преподаватели – молодые кандидаты наук, выпускники кафедры к.ф.-м.н. Александр Адуенко, к.ф.-м.н. Олег Бахтеев, к.ф.-м.н. Роман Исаченко, соискатель к.ф.-м.н. Андрей Грабовой. Средний возраст преподаватетей 35 лет.

+ +

Направления учебной и научной деятельности кафедры

+

Машинное обучение; многомерная статистика; геометрические методы глубокого обучения; выбор моделей и нейросетевых архитектур; ансамбли моделей и порождающие нейросети; функциональный анализ данных и анализ пространственно-временных данных.

+ +

Прикладные исследования

+

Анализ текстов и тематическое моделирование, анализ изображений и видео, анализ многомерных временных рядов, анализ биомедицинских сигналов, интерфейсы мозг-компьютер.

+ +

Принципы научной работы

+

Открытость идей, проектов, результатов на всех стадиях учебы и исследований; постоянная оценка качества идей и результатов; связь с научным сообществом, обновление согласно последним достижениям.

+ +

Основные курсы

+

Машинное обучение читает К.В. Воронцов – наиболее известный в России и полный курс, включающий фундаментальные и современные темы машинного обучения и анализа данных.

+ +

Моя первая научная статья: автоматизация научных исследований читает В.В. Стрижов – курс, дающий основы выполнения научных исследований – от планирования до представления результатов. Каждый студент выбирает персональный проект и получает личного консультанта и эксперта. В течение трех месяцев студент готовит научную статью с теорией и вычислительным экспериментом. Результаты представляются на научных конференциях, статьи подаются в рецензируемые журналы.

+ +

Основные курсы (программы)

+ + +

Стипендии

+ + +

Совместные учебные программы

+

В 2019 году кафедрой организована программа двойных дипломов и совместной магистратуры в Университете Гренобль-Альпы. Студенты магистратуры обучаются по совместным программам в Парижской политехнической школе, Сколковском институте науки и технологий, Научно-технологическом университете KAUST. Ведутся совместные исследования с лабораториями UGA, INRIA, CNRS, Ecole Polytechnique, EPFL, Los-Alamos, CMU.

+ + +

Стажировки

+

Кафедра с момента своего основания активно сотрудничает с базовыми компаниями группы Форексис ГК: Форексис, Антиплагиат, Антирутина, Гудфокаст, Лаборатория труда, Прокомплаенс и участвует в совместных проектах Форексис ГК с компаниями ММФБ, ИнтерРАО, Яндекс, Сбер, РЖД, Samsung, LG.

+ + +

Приходите к нам учиться и заниматься научными исследованиями в области машинного обучения!

+ + + + + +
+ + +
+ + diff --git a/ru/admission/index.html b/ru/admission/index.html new file mode 100644 index 00000000..08ad62ac --- /dev/null +++ b/ru/admission/index.html @@ -0,0 +1,379 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Поступающим + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + +

Слушателям отдельных курсов

+
    +
  1. Приходите, слушайте, участвуйте.
    2. +
  2. Вся информация о текущих курсах доступна в канале.
    3. +
  3. Ведомости на кафедру идут из деканата, оформляйте их там.
    4. +
  4. Курсы требуют подготовки, поэтому +
      +
    • уточните у преподавателей возможность присоединиться к курсу,
      • +
    • в течение первых недель поймите, сможете ли вы сдать курс.
      • +
    +
    5. +
  5. Узнайте, что требуется для сдачи курса.
    6. +
+ + + + + + +

Поступление на кафедру

+

Формат поступления: собеседование

+ +

Алгоритм поступления, 2-3 курсы, бакалавры

+ +
    +
  1. студент заполняет анкету,
    2. +
  2. решает одну из нижеприведенных задач (четвертый курс рассказывает о дипломной работе),
    3. +
  3. составляет мнение о работах, которые выполняют студенты кафедры,
    4. +
  4. в назначенную дату делает трехминутный доклад о задаче и о заинтересовавшей теме или работе,
    5. +
  5. в тот же день вечером получает решение кафедры,
    6. +
  6. ждет распоряжение деканата о распределении на кафедру.
    7. +
+ +

Процедура собеседования 3 курса с точки зрения преподавателей

+
    +
  1. cобираем всю группу желающих поступить на кафедру,
    2. +
  2. слушаем краткий доклад каждого участника +
      +
    • «решение тестовой задачи»,
      • +
    • «мои цели при поступлении на кафедру» на материале студенческих работ кафедры,
      • +
    +
    3. +
  3. задаем вопросы, смотрим анкету,
    4. +
  4. составляем ранжированный список поступающих, публикуем [по ссылке тут] и отправляем в деканат.
    5. +
+ +

Материалы

+
    +
  1. дипломные работы, отчеты НИР,
    2. +
  2. презентации магистров, презентации бакалавров
    3. +
+ +

Пробные задачи осень 2024 и более ранние

+

Ссылка – осень 2024 будут тут же

+ +

Советы по решению задач (это просто советы, а не указания)

+ + +

Список тем для обсуждения

+

Собран в разделе Список тем на этой странице

+ +

Результаты отбора

+ + +

Процедура приема в магистратуру

+
    +
  1. студент заполняет анкету,
    2. +
  2. cобираем желающих поступить на кафедру по запросам от них,
    3. +
  3. смотрим анкету, дипломную работу, спрашиваем мнение о теме и работах студентов кафедры, задаем вопросы по математической части бакалаврской программы Разделы 1, 2, 3 из Pen and Paper Exercises in Machine Learning by Michael U. Gutmann
    4. +
+ +

Цель собеседования – понять,

+
    +
  1. каков вклад студент внесет в научную работу кафедры
    2. +
  2. соответствует ли квалификация студента уровню планируемых диссетраций магистров.
    3. +
+ +

Научная работа на кафедре

+ +

Ваша научная квалификация – ваша основная цель на кафедре. Кафедра фокусируется на математических основах машинного обучения. Это означает, что ваши результат, ваша работа фокусируется на развитии теоретических методов. Практические приложения для иллюстрации ваших результатов в вычислительном эксперименте могут быть произвольными.

+ +

Научное сотрудничество и обмен идеями являются основой научной работы. Не стесняйтесь писать исследователям и рассказывать о себе и своих результатах и планах. Цель научного руководителя для вас – показать верное направление для исследований, дать тему, поставить задачу в общем. Надо понимать, что руководитель работает в своей тематике. Как узнать тематику? В scholar.google.com забить фамилию руководителя, посмотреть работы последних лет. Попросить у руководителя задачу.

+ +

Требования к научному руководителю:  +1) доктор или кандидат наук,  +2) работает в тематике кафедры.

+ +

Кафедра не может назначить вам научного руководителя. Его надо найти путем общения и договоренности о совместной работе. Когда будете искать научных руководителей, рассказывайте о себе: каковы ваша квалификация, достижения, научные работы, планы.

+ +

Совет. Ищите научных руководителей в исследовательских группах. Если Вас интересуют

+ + +

Найдите участников этих научных групп. Посмотрите тематику их научных статей последних лет. Составьте список соавторов. Посмотрите прикрепленный PDF. Напишите потенциальным руководителям. Важный совет. Свяжитесь со студентами и аспирантами Вашей специальности. Спросите их как они организуют работу с научными руководителями. 

+ +

Для быстрого представления начальных результатов постарайтесь принять участие в студенческих конференциях пример.

+ +

Что надо сделать:

+
    +
  1. Посмотреть кто был успешным научруком: + +
    2. +
  2. Посоветоваться со студентами и аспирантами. Почитать руководство.
    3. +
  3. Найти научного руководителя (по вашему стилю мышления и интересам). 
    4. +
  4. Попросить его связаться с кафедрой и утвердить тему работы. 
    5. +
  5. Начать работу с ним и представить ее результаты на зачетной неделе в начале сессии. 
    6. +
  6. Формат отчетности статья, презентация, код.
    7. +
+ + + + +
+ + +
+ + diff --git a/ru/course/automation_scientific_research/index.html b/ru/course/automation_scientific_research/index.html new file mode 100644 index 00000000..bc6d1810 --- /dev/null +++ b/ru/course/automation_scientific_research/index.html @@ -0,0 +1,374 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Автоматизация научных исследований + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Автоматизация научных исследований

+
+ + + + + +
+ +

О курсе “Моя первая научная статья”

+

В рамках этого курса студент готовится к научной работе в области машинного обучения. Он работает в персональной исследовательской группе. Каждая группа состоит из студента, консультанта и эксперта. Цель курса – научиться точно, ясно, красиво излагать свои и чужие идеи. Задача – написать научную статью, которая была бы принята другими исследователями, работающими в нашей области; сделать доклад.

+ +

Страница курса

+ + +

Тематический план

+ + +

Самостоятельная работа

+

Личный проект в области прикладной математики или машинного обучения, выполняемый под руководством консультанта. Результат – научная статья, код, доклад.

+ +

Оценивание

+

Каждая неделя состоит из нескольких заданий. Выполнение задания дает один балл согласно расписанию.

+ +

Требуемые знания

+

Знание алгебры и математического анализа в объеме двух курсов ФУПМ МФТИ.

+ + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Стрижов Вадим Викторович +

+
+ + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/bayesian_model_selection/index.html b/ru/course/bayesian_model_selection/index.html new file mode 100644 index 00000000..29fa7fde --- /dev/null +++ b/ru/course/bayesian_model_selection/index.html @@ -0,0 +1,373 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Байесовский выбор моделей + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Байесовский выбор моделей

+
+ + + + + +
+ +

О курсе

+

Курс посвящен изучению основ байесовских методов машинного обучения, построения байесовских моделей данных и вывода в них. Рассматриваются оптимальные байесовские прогнозы, а также методы их построения. Освещаются способы учета нелинейностей и неоднородностей в данных, пропусков в данных, а также эволюции оптимальной модели во времени.

+ +

Темы

+ + +

Самостоятельная работа

+

4 теоретических задания (выполняются индивидуально), 1 практическое задание и 1 соревнование (выполняются по командам), 2 теста. +Письменный и устный экзамен (последний можно заменить докладом на тему по выбору).

+ +

Оценивание

+

Каждое теоретическое задание дает максимум 50 или 100 баллов, практическое и соревнование — до 150. Баллы автора лучшей работы удваиваются (дополнительные баллы). +Устный и письменный экзамен добавляют до 250 баллов. +Общая оценка рассчитывается шкалированием к максимально возможной без учета дополнительных баллов.

+ +

Требуемые знания

+

Знание теории вероятностей, основ машинного обучения, линейной алгебры и методов оптимизации.

+ + + +
+

Преподаватели

+
+ +
+ + + + +
+

+ + + + Адуенко Александр Александрович +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/bayesian_multimodeling/index.html b/ru/course/bayesian_multimodeling/index.html new file mode 100644 index 00000000..2cc97cd4 --- /dev/null +++ b/ru/course/bayesian_multimodeling/index.html @@ -0,0 +1,358 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Байесовское мультимоделирование + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Байесовское мультимоделирование

+
+ + + + + +
+ +

О курсе

+

Данный курс посвящен проблеме выбора моделей в задачах машинного обучения и анализа данных. В рамках курса рассматривается байесовский подход к задаче выбора моделей, его теоретические и практические аспекты. Рассматриваются особенности различных подходов к решению задач выбора, агрегации и композиции как для моделей специального вида, так и для общего вида моделей.

+ +

Тематический план

+

В курсе рассматриваются особенности выбора моделей для разных типов моделей: от линейных до смесей экспертов, построенных на моделях глубокого обучения. Рассматриваются различные подходы к выбору моделей и настройке гиперпараметров, включая градиентные методы, методы sequential model based optimization, методы на основе гиперсетей и суперсетей.

+ +

Самостоятельная работа

+

4 практических работы, 2 доклада по желанию каждый семестр. Каждую неделю также проводится анкетирование по итогам занятия.

+ +

Оценивание

+

Оценка складывается из практических заданий, докладов и ответов на анкету.

+ +

Требуемые знания

+

Статистика, линейная алгебра, машинное обучение, глубокое обучение, элементы байесовского вывода.

+ + + +
+

Преподаватели

+
+ +
+ + + + + + + + +
+

+ + + + Бахтеев Олег Юрьевич +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/bioinformatics/index.html b/ru/course/bioinformatics/index.html new file mode 100644 index 00000000..40bfd66c --- /dev/null +++ b/ru/course/bioinformatics/index.html @@ -0,0 +1,373 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Биоинформатика + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Биоинформатика

+
+ + + + + +
+ +

О курсе

+

В курсе лекций рассматриваются уникальные особенности биологических данных, приводящие к оригинальным постановкам задач распознавания и классификации. Следует отметить, что практически для всех рассматриваемых в курсе задач пока еще не было предложено точных и математически обоснованных решений. В этом смысле курс представляет обширное поле деятельности для самостоятельной научной работы студентов. +Формулируется система задач распознавания, отражающая структуру биологических систем и дающая основу для построения проблемно-ориентированных теорий. Рассматриваются основы формализма, разрабатываемого для решения задач биоинформатики и других плохо-формализованных задач из области перспективных биомедицинских исследований и сентимент-анализа. Данный формализм основан на теории универсальных и локальных ограничений в рамках алгебраического подхода к распознаванию. Уделяется внимание биомедицинским приложениям результатов интеллектуального анализа биологических данных.

+ +

Тематический план

+ + +

Самостоятельная работа

+

В ходе лекций будут объявляться практические задания. Студенты могут сами формулировать темы исследовательских задач. После выбора задачи, обсуждаются требования к работе.

+ +

Оценивание

+

До начала устного экзамена (отчет-презентация) необходимо сдать отчет об исследовательской работе (3-5 стр), проведенной по выбранной задаче.

+ +

Требуемые знания

+

Основыв машинного обучения.

+ + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Торшин Иван Юрьевич +

+
+ + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/computational_geometry/index.html b/ru/course/computational_geometry/index.html new file mode 100644 index 00000000..ce227366 --- /dev/null +++ b/ru/course/computational_geometry/index.html @@ -0,0 +1,366 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Алгоритмы вычислительной геометрии + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Алгоритмы вычислительной геометрии

+
+ + + + + +
+ +

О курсе

+

В курсе рассматриваются основные алгоритмы вычислительной геометрии.

+ +

Тематический план

+ + +

Самостоятельная работа

+

В курсе предполагается решение нескольких лабораторных работ.

+ +

Оценивание

+

Оценка выставляется по результатам лабораторных работ и устного экзамена.

+ +

Требуемые знания

+

Основы машинного обучения, структуры данных и алгоритмы.

+ + + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Местецкий Леонид Моисеевич +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/deep_generative_models/index.html b/ru/course/deep_generative_models/index.html new file mode 100644 index 00000000..f76e38cf --- /dev/null +++ b/ru/course/deep_generative_models/index.html @@ -0,0 +1,459 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Порождающие модели машинного обучения + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Порождающие модели машинного обучения

+
+ + + + + Страница курса
+ + +
+ +

О курсе

+

Курс посвящен современным генеративным моделям машинного обучения. +Особое внимание уделяется свойствам различных классов генеративных моделей, их взаимосвязям, теоретическим предпосылкам и методам оценки качества. +Цель курса - познакомить студента с широко используемыми передовыми методами построения порождающих моделей.

+ +

Тематический план

+
    +
  1. Введение в генеративное моделирование. Постановка задачи. Задача минимизации дивергенций. Авторегрессионное моделирование.
    2. +
  2. Авторегрессионные модели (WaveNet, PixelCNN). Основы байесовского вывода. Модели скрытых переменных. Вариационная нижняя оценка (ELBO).
    3. +
  3. EM-алгоритм, амортизированный вывод. Градиенты ELBO, репараметризация. Вариационный автокодировщик (VAE). 
    4. +
  4. Недостатки VAE. Коллапс апостериорного распределения VAE. Техники ослабления декодера. Выборка по значимости для ELBO. Якобиан и теорема о замене переменных.
    5. +
  5. Модели нормализующих потоков. Прямая и обратная KL дивергенции. Линейные потоки (Glow).
    6. +
  6. Авторегрессионные потоки (гауссовский и обраный гауссовский поток). Слой связи (RealNVP). Связь нормализующих потоков и VAE. 
    7. +
  7. Дискретные данные, непрерывная модель. Дискретизация модели (PixelCNN++). Равномерная и вариационная деквантизации (Flow++). Теорема об операции над ELBO. Оптимальное априорное распределение в VAE. Потоки в априорном распределении VAE.
    8. +
  8. Потоки в априорном и апостериорном распределении VAE. Неявные генеративные модели без оценки правдоподобия. Модель генеративных состязательных сетей (GAN). Теорема об оптимальности GAN.
    9. +
  9. Проблемы обучения GAN моделей (затухающие градиенты, коллапс мод). KL дивергенция vs JS дивергенция. VAE с неявным энкодером. Топологические особенности обучения GAN моделей. Расстояние Вассерштейна. Дуальность Канторовича-Рубинштейна. GAN Вассерштейна (WGAN).
    10. +
  10. Модель WGAN с градиентным штрафом. Модель WGAN со спектральной нормализацией. Вариационная минимизация f-дивергенций. Оценивание качества неявных моделей.
    11. +
  11. Оценивание качества неявных моделей (Inception score, FID, Precision-Recall, truncation trick). VAE с дискретным скрытым пространством.
    12. +
  12. Векторная квантизация, сквозной градиент (VQ-VAE). Гумбель-софтмакс трюк (DALL-E). Нейронные обыкновенные дифференциальные уравнения. Метод сопряженных функций.
    13. +
  13. Непрерывные во времени нормализационные потоки (FFJORD). Несмещенная оценка следа матрицы. Основы стохастических дифференциальных уравнений. Уравнение Колмогорова-Фоккера-Планка и динамика Ланжевена. Методы оценивания score функции.
    14. +
  14. Модели оценки score функции (NCSM). Гауссовский диффузионый процесс. Диффузионная генеративная модель (DDPM).
    15. +
+ +

Cамостоятельная работа

+

6 домашних работ, каждая содержит как теоретические задания, так и практические.

+ +

Оценивание

+

Каждая домашняя работа дает 13 баллов + экзамен на 26 баллов. Финальная оценка: (количество баллов / 8) - 2.

+ +

Требуемые знания

+

Статистика, машинное обучение, глубокое обучение, элементы байесовского вывода.

+ + + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Исаченко Роман Владимирович +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Мокров Петр Владимирович +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/deep_learning/index.html b/ru/course/deep_learning/index.html new file mode 100644 index 00000000..387d5b6e --- /dev/null +++ b/ru/course/deep_learning/index.html @@ -0,0 +1,696 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Методы глубокого обучения + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Методы глубокого обучения

+
+ + + + + +
+ +

О курсе

+

Обзорный курс по основным нейросетевым моделям и их применению к различным задачам обработки изображений, текста, звука.

+ +

Тематический план

+ + +

Самостоятельная работа

+

Всего в семестре предполагается 5 практических заданий. Каждое задание оценивается из 10-ти баллов. Все задания можно сдать спустя неделю после мягкого дедлайна со штрафом 0.3 балла в день. Экзамен оценивается из 10-ти баллов.

+ +

Оценивание

+

0.7 * баллы за семестр + 0.3 * баллы за экзамен.

+ +

Требуемые знания

+

Машинное обучение, статистика, методы оптимизации.

+ + + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Кропотов Дмитрий Александрович +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Гребенькова Ольга Сергеевна +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Филатов Андрей Викторович +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Бишук Антон Юрьевич +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Яковлев Константин Дмитриевич +

+
+ + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/forecasting_methods/index.html b/ru/course/forecasting_methods/index.html new file mode 100644 index 00000000..4508d0f9 --- /dev/null +++ b/ru/course/forecasting_methods/index.html @@ -0,0 +1,535 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Математические методы прогнозирования + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Математические методы прогнозирования

+
+ + + + + +
+ +

О курсе

+

Курс построен на примерах задач построения интерфейса мозг-компьютер и прогнозирования пространственно-временных рядов. Методы машинного обучения рассматриваются с точек зрения физики и прикладной математики. Изучаются элементы тензорного представления данных, функционального и геометрического анализа данных.

+ +

Тематический план

+ + +

Самостоятельная работа

+

Две персональных лабораторных работы по анализу данных головного мозга с постановкой задачи и вычислительным экспериментом. Отчет состоит из двухстраничного описания результатов, кода и доклада.

+ +

Оценивание

+

Вопросы в течение занятий (3), две лабораторные работы (2+2), экзамен в конце с обсуждением тем и задач (3).

+ +

Требуемые знания

+

Знание алгебры, математического анализа и общей физики в объеме трех курсов ФУПМ МФТИ.

+ +

Страница курса

+

с подробным расписанием и материалами

+ + + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Стрижов Вадим Викторович +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Самохина Алина Максимовна +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Тихонов Денис Максимович +

+
+ + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/fundamental_ml_theorems/index.html b/ru/course/fundamental_ml_theorems/index.html new file mode 100644 index 00000000..f7972877 --- /dev/null +++ b/ru/course/fundamental_ml_theorems/index.html @@ -0,0 +1,375 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Фундаментальные теоремы машинного обучения + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Фундаментальные теоремы машинного обучения

+
+ + + + + +
+ +

О курсе

+

Цель курса – научиться строго формулировать задачи машинного обучения и показать роль математического подхода. Навыки, полученные на этом курсе являются основой при написании квалификационных работ бакалавра, магистра и кандидата наук. Курс включает обсуждение аксиоматических систем, теорем и их доказательств, имеющих значение в машинном обучении. Обсуждается их влияние на практические приложения.

+ +

Тематический план

+ + +

Самостоятельная работа

+

Подготовка и чтение докладов с формулировками, доказательствами и способами применения, значимостью, теорем

+ +

Оценивание

+

Оценивается качество докладов и качество вопросов к докладчику каждого студента

+ +

Требуемые знания

+

Алгебра и анализ третьего курса МФТИ

+ + + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Стрижов Вадим Викторович +

+
+ + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/image_processing_recognition/index.html b/ru/course/image_processing_recognition/index.html new file mode 100644 index 00000000..3645a91c --- /dev/null +++ b/ru/course/image_processing_recognition/index.html @@ -0,0 +1,373 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Обработка и распознавание изображений + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Обработка и распознавание изображений

+
+ + + + + +
+ +

О курсе

+

Основу курса составляют математические методы распознавания образов, используемые для анализа и классификации изображений в системах компьютерного зрения. +Рассматриваются преобразования изображений с целью генерации признаковых описаний. Изучаются методы точечной, пространственной геометрической, алгебраической и межкадровой обработки изображений. Рассматриваются методы генерации признаков на основе разложения изображений по базисным функциям, статистического анализа текстуры изображений, а также анализа формы изображений. +Рассматриваются методы построения метрик для сравнения изображений (сравнение спектральных разложений, наложение и выравнивание образов). А также вопросы применения изученных методов в прикладных задачах компьютерного зрения. Рассматриваются задачи распознавания текстов в изображениях документов, задачи биометрической идентификации личности по текстуре радужной оболочки глаза, по форме ладони, отпечатка пальца, профиля лица.

+ +

Тематический план

+ + +

Самостоятельная работа

+

Вычислительный практикум по обработке и классификации изображений.

+ +

Оценивание

+

Оценка выставляется по результатам лабораторных работ и устного экзамена.

+ +

Требуемые знания

+

Основы машинного обучения, линейная алгебра.

+ + + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Местецкий Леонид Моисеевич +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/index.html b/ru/course/index.html new file mode 100644 index 00000000..ca5bcce8 --- /dev/null +++ b/ru/course/index.html @@ -0,0 +1,557 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Курсы + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Бакалавриат

+
+
+ +
+ + + +
+

+ Автоматизация научных исследований +

+
+ + + + + +
+

+ Байесовский выбор моделей +

+
+ + + + + + + + + + + + + +
+

+ Методы глубокого обучения +

+
+ + + + + +
+

+ Математические методы прогнозирования +

+
+ + + + + + + + + + + +
+

+ Введение в машинное обучение +

+
+ + + + + + + +
+

+ Анализ сетей и текстов +

+
+ + + + + + + +
+

+ Методы оптимизации в машинном обучении +

+
+ + + + + + + +
+

+ Рекомендательные системы +

+
+ + + + + + + + + +
+ +
+

Магистратура

+
+
+ +
+ + + + + + + +
+

+ Байесовское мультимоделирование +

+
+ + + + + +
+

+ Биоинформатика +

+
+ + + + + + + +
+

+ Порождающие модели машинного обучения +

+
+ + + + + + + + + + + + + +
+

+ Интеллектуальный анализ данных +

+
+ + + + + + + +
+

+ Математические методы анализа текстов +

+
+ + + + + + + + + + + +
+

+ Вероятностные тематические модели +

+
+ + + + + + + +
+

+ Создание интеллектуальных систем +

+
+ + + + + +
+

+ Обработка сигналов +

+
+ + + + + +
+

+ Программная инженерия для анализа данных +

+
+ + + +
+ +
+

Больше не преподаются

+
+
+ +
+ + + + + + + + + + + +
+

+ Алгоритмы вычислительной геометрии +

+
+ + + + + + + + + + + +
+

+ Фундаментальные теоремы машинного обучения +

+
+ + + + + +
+

+ Обработка и распознавание изображений +

+
+ + + + + + + + + + + + + +
+

+ Поиск нейросетевых архитектур +

+
+ + + + + + + + + + + + + + + +
+ + + + +
+ + +
+ + diff --git a/ru/course/intellectual_data_analysis/index.html b/ru/course/intellectual_data_analysis/index.html new file mode 100644 index 00000000..7bc57546 --- /dev/null +++ b/ru/course/intellectual_data_analysis/index.html @@ -0,0 +1,432 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Интеллектуальный анализ данных + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Интеллектуальный анализ данных

+
+ + + + + +
+ +

О курсе

+

Курс вводит студентов в полный цикл создания моделей машинного обучения для исследовательских целей. +Основные этапы семестра: анализ прикладной проблемы и постановка задачи, построение модели, выполнение вычислительного эксперимента, анализ ошибки. +Результатом работы группы студентов является библиотека моделей для фиксированной прикладной задачи или класса задач.

+ +

Страница курса

+ +

Самостоятельная работа

+

Оценивается: квалификация студента и его личный вклад в проект.

+ + + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Стрижов Вадим Викторович +

+
+ + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Бахтеев Олег Юрьевич +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/introduction_machine_learning/index.html b/ru/course/introduction_machine_learning/index.html new file mode 100644 index 00000000..333bdbab --- /dev/null +++ b/ru/course/introduction_machine_learning/index.html @@ -0,0 +1,383 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Введение в машинное обучение + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Введение в машинное обучение

+
+ + + + + Страница курса
+ + +
+ +

О курсе

+

В курсе рассматриваются основные задачи обучения по прецедентам: классификация, кластеризация, регрессия, понижение размерности. Изучаются методы их решения, как классические, так и новые, созданные за последние 10–15 лет. Упор делается на глубокое понимание математических основ, взаимосвязей, достоинств и ограничений рассматриваемых методов. Теоремы в основном приводятся без доказательств.

+ +

Тематический план

+ + +

Самостоятельная работа

+

Нет.

+ +

Оценивание

+

В конце курса студенты сдают устный экзамен по всем темам курса.

+

Требуемые знания

+ +

Теория вероятностей, статистика, методы оптимизации, линейная алгебра.

+ + + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Воронцов Константин Вячеславович +

+
+ + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/natural_language_processing/index.html b/ru/course/natural_language_processing/index.html new file mode 100644 index 00000000..66736bad --- /dev/null +++ b/ru/course/natural_language_processing/index.html @@ -0,0 +1,445 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Математические методы анализа текстов + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Математические методы анализа текстов

+
+ + + + + +
+ +

О курсе

+

В курсе рассматриваются основные задачи и математические методы обработки естественного языка.

+ +

Тематический план

+ + +

Самостоятельная работа

+

В рамках курса предполагается четыре практических задания и экзамен. Срок выполнения каждого задания — 2 недели. За каждое задание можно получить до 10-ти баллов. За каждый день просрочки назначается штраф 1 балл.

+ +

Оценивание

+

0.7 * баллы за дз / 5 + 0.3 * баллы за экзамен.

+ +

Требуемые знания

+

Машинное обучение, основы глубинного обучения, языка программирования Python.

+ + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Попов Артем Сергеевич +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/networks_text_analysis/index.html b/ru/course/networks_text_analysis/index.html new file mode 100644 index 00000000..dfa45997 --- /dev/null +++ b/ru/course/networks_text_analysis/index.html @@ -0,0 +1,373 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Анализ сетей и текстов + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Анализ сетей и текстов

+
+ + + + + +
+ +

О курсе

+

Рассматриваются методы и технологии, применяющиеся в интеллектуальном анализе данных (ИАД, data mining) и базирующиеся на понятиях сходства, близости, аналогии. Идея сходства свойственна человеческому мышлению, это породило целый комплекс подходов для всех фундаментальных задач ИАД, среди которых основное внимание в курсе уделено классификации, восстановлению регрессии, кластеризации, восстановлению пропущенных данных. +Представлена теоретическая основа для построения, реализации и анализа широкого спектра моделей и методов ИАД. Рассмотрены методы построения и вычисления функций сходства, согласование сходства на различных множествах объектов, синтез новых способов сравнения объектов на базе уже имеющихся. Рассмотрен комплекс технологий, предназначенный для эффективного представления и обработки метрической информации вычислительными системами. +Исследуются эвристические модели данных, описывающие исходную информацию об объектах распознавания на основе различных реализаций понятия сходства. Рассматриваются задачи, требующие решения при реализации указанных моделей. Изучаются специальные структуры данных и алгоритмы, позволяющие эффективно настраивать и использовать изучаемые модели.

+ +

Тематический план

+ + +

Самостоятельная работа

+

Нет.

+ +

Оценивание

+

Устный экзамен по материалам курса.

+ +

Требуемые знания

+

Машинное обучение, алгоритмы и структуры данных.

+ + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Майсурадзе Арчил Ивериевич +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/neural_architecture_search/index.html b/ru/course/neural_architecture_search/index.html new file mode 100644 index 00000000..6fa0fcc4 --- /dev/null +++ b/ru/course/neural_architecture_search/index.html @@ -0,0 +1,372 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Поиск нейросетевых архитектур + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Поиск нейросетевых архитектур

+
+ + + + + +
+ +

О курсе

+

Курс посвящен современным методам построения сложных нейросетевых архитектур и выбору оптимальных структур.

+ +

Тематический план

+ + +

Самостоятельная работа

+

Лабораторная работа состоит в исследовании метода поиска архитектуры. Первая работа – проанализировать готовый метод, вторая работа – предложить и запрограммировать свой метод. Отчет о работе – страница текста с формальным описанием метода с детализацией, достаточной для восстановления кода, и анализом ошибки (базовые критерии сложность, устойчивость, точность). Интерфейс к классу фиксирован и общий для всех, так же как и выборки. Существует общая таблица с результатами, и частный анализ ошибки каждого метода.

+ +

Оценивание

+

Всего 10 баллов, два балла за ответы на вопросы в течение лекций, по четыре балла за две лабораторные работы. Оценивается не точность аппроксимации, а качество кода и анализ ошибки.

+ +

Требуемые знания

+

Машинное обучение, глубокое обучение, байесовский выбор моделей.

+ + + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Потанин Марк Станиславович +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/optimization_methods/index.html b/ru/course/optimization_methods/index.html new file mode 100644 index 00000000..e5288ae3 --- /dev/null +++ b/ru/course/optimization_methods/index.html @@ -0,0 +1,354 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Методы оптимизации в машинном обучении + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Методы оптимизации в машинном обучении

+
+ + + + + +
+ +

О курсе

+ +

Тематический план

+ +

Самостоятельная работа

+ +

Оценивание

+ +

Требуемые знания

+ + + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + +
+

+ + + + Безносиков Александр Николаевич +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/probabilistic_topic_models/index.html b/ru/course/probabilistic_topic_models/index.html new file mode 100644 index 00000000..be3e8d4a --- /dev/null +++ b/ru/course/probabilistic_topic_models/index.html @@ -0,0 +1,371 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Вероятностные тематические модели + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Вероятностные тематические модели

+
+ + + + + +
+ +

О курсе

+

В спецкурсе изучается вероятностное тематическое моделирование (topic modeling) коллекций текстовых документов. Тематическая модель определяет, какие темы содержатся в большой текстовой коллекции, и к каким темам относится каждый документ. Тематические модели позволяют искать тексты по смыслу, а не по ключевым словам, и создавать информационно-поисковые системы нового поколения, основанные на парадигме семантического разведочного поиска (exploratory search). Рассматриваются тематические модели для классификации, категоризации, сегментации, суммаризации текстов естественного языка, а также для рекомендательных систем, анализа банковских транзакционных данных, анализа биомедицинских сигналов. В спецкурсе развивается многокритериальный подход к построению моделей с заданными свойствами — аддитивная регуляризация тематических моделей (АРТМ). Он основан на регуляризации некорректно поставленных задач стохастического матричного разложения. Особое внимание уделяется методам лингвистической регуляризации для моделирования связности текста. Предполагается проведение студентами численных экспериментов на модельных и реальных данных с помощью библиотеки тематического моделирования BigARTM.

+ +

Тематический план

+ + +

Самостоятельная работа

+

Нет.

+ +

Оценивание

+

Условием сдачи курса является выполнение индивидуальных практических заданий.

+ +

Требуемые знания

+

Линейная алгебра, математический анализ, теория вероятностей.

+ + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Воронцов Константин Вячеславович +

+
+ + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/recommender_systems/index.html b/ru/course/recommender_systems/index.html new file mode 100644 index 00000000..2af7d064 --- /dev/null +++ b/ru/course/recommender_systems/index.html @@ -0,0 +1,451 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Рекомендательные системы + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Рекомендательные системы

+
+ + + + + Страница курса
+ + +
+ +

О курсе

+

Курс посвящен рекомендательным системам. Мы рассмотрим основные теоретические и прикладные аспекты задачи рекомендаций. В конце немного затронем применение многоруких бандитов для рекомендаций и специфические вопросы оценивания рекомендательных систем.

+ +

Тематический план

+
    +
  1. Задача рекомендаций
    2. +
  2. Модели, основанные на методе ближайших соседей
    3. +
  3. Матричная факторизация
    4. +
  4. Модели, основанные на контенте и гибридные модели
    5. +
  5. Двухуровневые модели
    6. +
  6. Нейросетевые модели рекомендаций
    7. +
  7. Многорукие бандиты в задаче рекомендаций
    8. +
  8. Оффлайн-оценивание рекомендаций
    9. +
+ +

Cамостоятельная работа

+

Два домашних задания по ходу курса

+ +

Оценивание

+

По результатам домашних заданий

+ +

Требуемые знания

+

Машинное обучение, глубокое обучение

+ + + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Гришанов Алексей Владимирович +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Володкевич Анна Алексеевна +

+
+ + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/rnd_in_ai/index.html b/ru/course/rnd_in_ai/index.html new file mode 100644 index 00000000..7d2b27ee --- /dev/null +++ b/ru/course/rnd_in_ai/index.html @@ -0,0 +1,401 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Создание интеллектуальных систем + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Создание интеллектуальных систем

+
+ + + + + Страница курса
+ + +
+ +

О курсе

+

Курс является расширением курса ``Автоматизация научных исследований’’. +Работа производится в командах — 2-3 человека. +Курс предполагает еженедельные презентации работы команды за неделю: 5 минут презентация + 5 минут обсуждение с другими людьми.

+ +

Критерий к проекту:

+
    +
  1. Весь проект должен быть на GitHub под OpenSource лицензией (MIT)
    2. +
  2. Проект должен содержать код и инструкция по его запуску. +
      +
    1. Базовый код в jupyter notebook для демонстрации концепции работы и построения графиков из статьи — должен запускаться с colab.
      2. +
    2. Исходный код вычислительного эксперимента должен запускаться на Unix системе выполнением двух команд (возможно в специльном docker образе): +
        +
      • python3 train.py — для обучения моделей.
        • +
      • python3 test.py — для тестирования, получения результатов эксперимента.
        • +
      +
      3. +
    3. Документация к коду — sphinx.
      4. +
    +
    3. +
  3. Проект должен содержать рукопись статьи используя стилевик от arXiv — для унификации.
    4. +
  4. Если проект подразумевает не синтетические данные, то должна быть инструкция для получения этих данных, а также скрипт для их получения. Если данные специфичные, то их требуется выложить на одном из файловых хранилищ.
    5. +
+ +

Тематический план

+
    +
  1. Вводная лекция.
    2. +
  2. Обсуждения проектов.
    3. +
  3. Правильная структура проекта.
    4. +
  4. Первый чекпоинт репозиторием.
    5. +
  5. Структура статьи.
    6. +
  6. Как правильно построить jupyter notebook.
    7. +
  7. Второй чекпоинт репозиторием.
    8. +
  8. Правильный код - код не в jupyter notebook!
    9. +
  9. О хранении данных для эксперимента.
    10. +
  10. Третий чекпоинт репозиторием.
    11. +
  11. Документация кода при помощи sphinx.
    12. +
  12. Докеризация кода эксперимента.
    13. +
  13. Четвертый чекпоинт репозиторием.
    14. +
  14. Проверка проектов и зачет.
    15. +
+ +

Самостоятельная работа

+

Написание статьи в рамках команды.

+ +

Grading

+

В курсе 4 чекпоинтов, за каждый дается 3 балла +Исследование предметной области — анализ проблемы. +Получение теоретических результатов. +Подготовка вычислительного эксперимента. +Проект на гитхабе.

+ +

Требуемые знания

+

Машинное обучение, глубокое обучение, программирование на питоне.

+ + + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Грабовой Андрей Валериевич +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/signal_processing/index.html b/ru/course/signal_processing/index.html new file mode 100644 index 00000000..124c3651 --- /dev/null +++ b/ru/course/signal_processing/index.html @@ -0,0 +1,368 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Обработка сигналов и многомерных массивов данных + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Обработка сигналов

+
+ + + + + +
+ +

О курсе

+

Курс посвящен использованию методов математического моделирования и теоретической физики в задачах обработки сигналов. На примерах изображений, видео, звука и других сигналов рассматриваются методы выбора моделей машинного обучения. Обсуждаются приемы построения систем моделей для разнородных сигналов.

+ +

Тематический план

+ + +

Самостоятельная работа

+

Две персональных лабораторных работы по анализу видеоряда с постановкой задачи и вычислительным экспериментом. Отчет состоит из двухстраничного описания результатов, кода и доклада.

+ +

Оценивание

+

Вопросы в течение занятий (3), две лабораторные работы (2+2), экзамен в конце с обсуждением тем и задач (3).

+ +

Требуемые знания

+

Знание алгебры, математического анализа и общей физики в объеме бакалавриата ФУПМ МФТИ.

+ + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Стрижов Вадим Викторович +

+
+ + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/course/software_engineering_data_analysis/index.html b/ru/course/software_engineering_data_analysis/index.html new file mode 100644 index 00000000..d0e6b1b0 --- /dev/null +++ b/ru/course/software_engineering_data_analysis/index.html @@ -0,0 +1,372 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Программная инженерия для анализа данных + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Программная инженерия для анализа данных

+
+ + + + + +
+ +

О курсе

+

В курсе рассматриваются вопросы разработки систем обработки данных и машинного обучения.

+ + +

В результате освоения курса слушатели приобретают навыки промышленной разработки алгоритмов машинного обучения, проведения повторяемых экспериментов, использования больших данных, тестирования и процессов выполнения проектов в области машинного обучения.

+ +

Тематический план

+ + +

Самостоятельная работа

+

Практические задания по ходу курса + курсовой проект.

+ +

Оценивание

+

Итоговая оценка по курсу формируется из успешности выполнения заданий по ходу семестра - по 10% за каждое задание, и подтверждение на устном опросе владения каждой из тем курса (CODE, TEST, DATA, PROC) - 40% оценки.

+ +

Требуемые знания

+

Python.

+ + + +
+

Преподаватели

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Хританков Антон Сергеевич +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + +
+ + diff --git a/ru/docker_test.sh b/ru/docker_test.sh new file mode 100644 index 00000000..3ee93dbd --- /dev/null +++ b/ru/docker_test.sh @@ -0,0 +1,3 @@ +# this is an extremely ineffective one-liner for testing our site +docker run --rm -it -v $(pwd):/data -p 4000:4000 -e LANG=C.UTF-8 -it ubuntu:20.04 /bin/bash -c "cd /data; apt-get update; apt-get install -y bundler; bundle install; bundle exec jekyll serve --host 0.0.0.0" + diff --git a/ru/education/index.html b/ru/education/index.html new file mode 100644 index 00000000..ff80ef4b --- /dev/null +++ b/ru/education/index.html @@ -0,0 +1,582 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Учебный процесс + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
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+ + + + + + + + + + +
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Расписание

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Осенний семестр, 2024

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Занятия онлайн

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Расписание занятий

+ +

4 курс, 7 семестр - вторник

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ВремяПредметПреподавателиФорма отчетностиЗачетные единицы
10:30-12:00Методы глубокого обучения: лекцияФилатов А.В., Яковлев К.Д.Дифф. зачет2
12:10-13:40Методы глубокого обучения: семинарФилатов А.В., Яковлев К.Д.  
14:30-16:00Байесовский выбор моделейАдуенко А.А., Яковлев К.Д.Дифф. зачет1
16:10-17:40Математические методы прогнозированияСамохина А.М., Тихонов Д.М.Дифф. зачет1
+ +

5 курс, 9 семестр - вторник

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ВремяПредметПреподавателиФорма отчетностиЗачетные единицы
14:30-16:00Создание интеллектуальных системГрабовой А.В.Дифф. зачет2
16:10-17:40Байесовское мультимоделированиеБахтеев О.Ю.Дифф. зачет2
18:00-19:30Порождающие модели машинного обучения: лекцияИсаченко Р.В., Кондратенко В.Экзамен3
19:30-21:00Порождающие модели машинного обучения: семинарИсаченко Р.В., Кондратенко В.  
+ +

6 курс, 11 семестр - четверг

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ВремяПредметПреподавателиФорма отчетностиЗачетные единицы
10:30-12:00Обработка сигналовСеверилов П.А.Экзамен3
12:10-13:40Интеллектуальный анализ данныхСтрижов В.В., Бахтеев О.Ю.Зачет2
14:30-16:00Вероятностные тематические моделиВоронцов К.В.Дифф. зачет2
+ +

Ключевые даты

+ + +

Весенний семестр, 2025

+ +

3 курс, 6 семестр – четверг

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ВремяПредметПреподавателиФорма отчетностиЗачетные единицы
12:10-13:40Введение в машинное обучениеГрабовой А.В., Воронцов К.В.Дифф. зачет1
14:30-16:00Практикум по программированию на языке ПитонАпишев М.А.Зачет1
16:10-17:40Создание интеллектуальных системГрабовой А.В.Зачет1
17:50-19:20Автоматизация научных исследований (Моя первая научная статья)Грабовой А.В., Бахтеев О.Ю.Дифф. зачет1
+ +

4 курс, 8 семестр – вторник

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ВремяПредметПреподавателиФорма отчетностиЗачетные единицы
10:30-12:00Рекомендательные системыГришанов А.В., Володкевич А.А.Дифф. зачет2
12:50-14:20Методы оптимизации в машинном обученииБезносиков А.Н.Дифф. зачет1
14:30-16:00Байесовский выбор моделейАдуенко А.А.Экзамен2
16:10-17:40Математические методы прогнозированияСамохина А.М.Дифф. зачет3
+ +

5 курс, 10 семестр – вторник

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ВремяПредметПреподавателиФорма отчетностиЗачетные единицы
10:30-12:00БиоинформатикаТоршин И.Ю.Дифф. зачет1
12:50-14:20Методы оптимизации в машинном обученииБезносиков А.Н.Дифф. зачет2
14:30-16:00Байесовское мультимоделированиеБахтеев О.Ю.Экзамен2
16:10-17:40Планирование проектов по созданию программного обеспеченияХританков А.С.Дифф. зачет1
17:50-19:20Создание интеллектуальных системГрабовой А.А.Экзамен2
+ +

Ключевые даты

+

+ +

+ + +

Документы и ссылки

+ + + + + +
+ + +
+ + diff --git a/ru/feed.xml b/ru/feed.xml new file mode 100644 index 00000000..30079659 --- /dev/null +++ b/ru/feed.xml @@ -0,0 +1 @@ +Jekyll2024-12-21T07:37:23+00:00https://intsystems.github.io/ru/feed.xml \ No newline at end of file diff --git a/ru/git-lfs-3.1.4-r5.apk b/ru/git-lfs-3.1.4-r5.apk new file mode 100644 index 00000000..c509499c Binary files /dev/null and b/ru/git-lfs-3.1.4-r5.apk differ diff --git a/ru/index.html b/ru/index.html new file mode 100644 index 00000000..9a8f0f51 --- /dev/null +++ b/ru/index.html @@ -0,0 +1,262 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Интеллектуальные системы + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ +
+ +
+ + + + +

Расписание занятий

+ +

Кафедра интеллектуальных систем выпускает бакалавров и магистров по направлению «Прикладные математика и физика».

+ +

Объявления и информация

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Занятия:

+ + + + + +
+ + +
+ + diff --git a/ru/materials/conferences/index.html b/ru/materials/conferences/index.html new file mode 100644 index 00000000..f44161ee --- /dev/null +++ b/ru/materials/conferences/index.html @@ -0,0 +1,4593 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Список конференций + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + +

Conferences & Journals on scientific topics of the department

+ +

The conferences mainly are retrieved from here http://www.guide2research.com/topconf/ (+ CORE2021: https://www.core.edu.au/conference-portal + some Russian and conferences well known by me).

+ +

The journals are retrieved from here https://www.scimagojr.com/journalrank.php.

+ +

References:

+
    +
  1. https://tinyurl.com/bahleg-conf
    2. +
  2. https://tinyurl.com/bahleg-journals
    3. +
+ +

Conferences

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Conference nameCategoryConference programURLRankRank system
SIGBOVIKSpecific http://sigbovik.org/--
ECIR : European Conference on Information RetrievalIR/MiningDemo, Industrial, Tutorials, Workshopshttps://www.ecir2024.org/ACORE2021
SIGIR: International ACM SIGIR Conference on Research and Development in Information RetrievalIR/Mining https://sigir-2024.github.io/ACORE2021
WWW: International World Wide Web ConferencesIR/MiningDemo, StudentThesis / Doctor symposium, Tutorials, Workshopshttps://www2024.thewebconf.org/ACORE2021
ESWC : Extended Semantic Web ConferenceIR/Mining https://2024.eswc-conferences.org/ACORE2021
MSR : Mining Software RepositoriesIR/Mining, Specific https://2024.msrconf.org/ACORE2021
WSDM : ACM International Conference on Web Search and Data MiningIR/Mining https://www.wsdm-conference.org/2024/ACORE2021
PODS : ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database SystemsIR/MiningDemo, Industrial, Tutorials, Workshopshttps://2024.sigmod.org/ACORE2021
RecSys : ACM Conference on Recommender SystemsIR/MiningTutorials, Workshopshttps://recsys.acm.org/recsys24/ACORE2021
EDBT : International Conference on Extending Database TechnologyIR/MiningStudentThesis / Doctor symposium, Workshopshttps://edbt.org/ACORE2021
DASFAA : International Conference on Database Systems for Advanced ApplicationsIR/Mining https://www.dasfaa2024.org/BCORE2021
SSBSE : International Conference on Search based Software EngineeringIR/Mining https://ssbse.info/BCORE2021
UMAP : International Conference on User Modelling, Adaptation, and PersonalizationIR/Mining, Specific https://www.um.org/umap2024/BCORE2021
Pacific Asia Conference on Language, Information and ComputationIR/Mining  BCORE2021
International Conference on Formal Ontology in Information SystemsIR/Mining, Specific  BCORE2021
ADBIS : Advances in Databases and Information SystemsIR/MiningStudentThesis / Doctor symposium, Tutorials, Workshopshttps://conferences.sigappfr.org/adbis2024/BCORE2021
WISE : International Conference on Web Information Systems EngineeringIR/Mining https://wise2024-qatar.com/BCORE2021
Workshop on Logic, Language, Information and ComputationIR/Mining, NLP https://wollic2024.inf.unibe.ch/BCORE2021
EKAW : Knowledge Engineering and Knowledge ManagementIR/Mining  BCORE2021
TPDL : International Conference on Theory and Practice of Digital LibrariesIR/Mining  BCORE2021
International Conference on Knowledge-Based and Intelligent Information and Engineering SystemsIR/MiningWorkshopshttp://kes2024.kesinternational.org/BCORE2021
Asian Conference on Intelligent Information and Database SystemsIR/Mining https://aciids.pwr.edu.pl/2024/BCORE2021
ADMA : International Conference on Advanced Data Mining and ApplicationsIR/Mining https://adma2024.github.io/BCORE2021
WI : IEEE/WIC/ACM International Conference on Web IntelligenceIR/MiningSpecialSession, Workshops BCORE2021
International Symposium on Computer and Information SciencesIR/Mining https://www.iscsic.org/CCORE2021
European-Japanese Conference on Information Modelling and Knowledge BasesIR/Mining https://ejc2024.ds.musashino-u.ac.jp/CCORE2021
International Conference on Information Technology and ApplicationsIR/MiningSpecialSession, Workshopshttps://www.icita.world/#/CCORE2021
International Conference on Legal Knowledge and Information SystemsIR/Mining, Specific  CCORE2021
Asia Information Retrieval SymposiumIR/Mining  CCORE2021
TRECIR/Mining, NLP  --
ASONAM : International Conference on Advances in Social Network Analysis and MiningIR/Mining  --
IEEE International Conference on Information and AutomationIR/Mining, ML/CS, Specific  --
WebSci : ACM on Web Science ConferenceIR/MiningTutorials, Workshopshttps://websci24.org/--
ISWC : International Semantic Web ConferenceIR/MiningTutorials, Workshops --
BTAS : IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS)IR/Mining, Specific  --
RussirIR/Mining, NLP  --
Statistical and Scientific Database ManagementIR/Mining https://ssdbm.org/2024/--
International Conference on Information and Knowledge EngineeringIR/Mining, Specific  --
International Conference on the Theory of Information RetrievalIR/Mining  --
IJCB : International Joint Conference on BiometricsIR/Mining, SpecificDemo, StudentThesis / Doctor symposium, Tutorials --
CHIIR : Conference on Human Information Interaction and RetrievalIR/Mining https://chiir2024.github.io/--
Conference on Information Sciences and SystemsIR/Mining https://ee-ciss.princeton.edu/--
International Baltic Conference on Databases and Information SystemsIR/Mining  --
ICWSM : International Conference on Web and Social MediaIR/Mining https://www.icwsm.org/2024/index.html/--
BigMM : IEEE International Conference on Multimedia Big DataIR/Mining  --
SemEval : International Workshop on Semantic EvaluationCV, IR/Mining, NLP, Signal https://semeval.github.io/SemEval2024/--
AVSS : IEEE International Conference on Advanced Video and Signal-Based SurveillanceSignal https://zinc.cse.buffalo.edu/ubmdfl/AVSS2024/index.phpBCORE2021
MMSP : IEEE Workshop on Multimedia Signal ProcessingSignalDemo, SpecialSession BCORE2021
International Conference on Image and Signal ProcessingSignal https://csita2024.org/ispr/indexCCORE2021
IEEE Symposium on Computational intelligence for Multimedia Signal and Vision ProcessingSignal  CCORE2021
DCASE : Detection and Classification of Acoustic Scenes and EventsSignalContests, Workshops --
ISMIR : International Society for Music Information Retrieval ConferenceIR/Mining, Signal, SpecificTutorialshttps://ismir2024.ismir.net/--
EUSIPCO : European Signal Processing ConferenceSignalTutorials, Workshopshttps://eusipcolyon.sciencesconf.org/--
International Conference on Robotics, Vision, Signal Processing and Power Applications (was ROVPIA)Signal, Specific  --
ICASSP: International Conference on Acoustics, Speech and Signal ProcessingSignal https://2024.ieeeicassp.org/--
SLT : IEEE Spoken Language Technology WorkshopSignalContests, Demo, Hackaton, Workshops --
ACM Symposium on Eye Tracking Research and ApplicationsCV, Signal, Specific https://etra.acm.org/2024/--
International Conference on Advanced Technologies For Signal & Image ProcessingSignal  --
WASPAA : IEEE Workshop on Applications of Signal Processing to Audio and AcousticsSignal  --
SPAWCSignal https://spawc2024.org/--
APSIPA : Asia-Pacific Signal and Information Processing Association Annual Summit and ConferenceSignal  --
SSP : IEEE Statistical Signal Processing WorkshopSignal  --
INTERSPEECH: Conference of the International Speech Communication AssociationSignal https://interspeech2024.org/--
MIPR : IEEE Conference on Multimedia Information Processing and RetrievalIR/Mining, SignalTutorials, Workshops --
ACSSC : Asilomar Conference on Signals, Systems and ComputersML/CS, Signal  --
WCSP : International Conference on Wireless Communications and Signal ProcessingSignal  --
SAM : IEEE Sensor Array and Multichannel Signal Processing WorkshopSignal https://2024.ieeesam.org/--
ICME: International Conference on Multimedia and ExpoCV, NLP, Signal https://2024.ieeeicme.org/ACORE2021
EACL : Conference of the European Chapter of the Association for Computational LinguisticsNLP https://2024.eacl.org/ACORE2021
CoNLL: Conference on Computational Natural Language LearningNLP  ACORE2021
ACL: Annual Meeting of the Association for Computational LinguisticsNLP https://2024.aclweb.org/ACORE2021
EMNLP: Conference on Empirical Methods in Natural Language ProcessingNLPTBA ACORE2021
COLING: International Conference on Computational LinguisticsNLPTutorials, Workshopshttps://lrec-coling-2024.org/ACORE2021
NAACL: North American Chapter of the Association for Computational LinguisticsNLPDemo, Industrial, Workshopshttps://2024.naacl.org/ACORE2021
SIGDIAL : Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)NLPSpecialSessionhttps://2024.sigdial.org/BCORE2021
IJCNLP : International Joint Conference on Natural Language Processing (IJCNLP)NLPTutorials, Workshops B-
DAS : IAPR International Workshop on Document Analysis SystemsNLPSpecialSession BCORE2021
NLDB : International Conference on Applications of Natural Language to Information SystemsNLP https://nldb2024.di.unito.it/CCORE2021
LREC : International Conference on Language Resources and Evaluation (LREC)NLP, Signal https://lrec-coling-2024.org/CCORE2021
DialogueNLPContestshttp://www.dialog-21.ru/--
CLEF : International Conference of the Cross-Language Evaluation Forum for European LanguagesCV, IR/Mining, NLP, Signal https://clef2024.clef-initiative.eu/--
SEM : Joint Conference on Lexical and Computational SemanticsNLP https://sites.google.com/view/starsem2024--
International Conference on Recent Advances in Natural Language ProcessingNLPTutorials, Workshops --
AINLNLP  --
IROS: International Conference on Intelligent Robots and SystemsCVTutorials, Workshops ACORE2021
ACMMM: ACM MultimediaCV, NLP, SignalDemo, StudentThesis / Doctor symposium, Workshops ACORE2021
ICCV: International Conference on Computer VisionCVTBA ACORE2021
ECCV: European Conference on Computer VisionCV https://eccv2024.ecva.net/ACORE2021
MICCAI : Medical Image Computing and Computer Assisted InterventionCV, Specific http://www.miccai.org/ACORE2021
ICDAR : International Conference on Document Analysis and RecognitionCV, IR/Mining, NLP https://icdar2024.net/ACORE2021
WACV: Winter Conference on Applications of Computer VisionCV https://wacv2024.thecvf.com/ACORE2021
CVPR: IEEE Conference on Computer Vision and Pattern RecognitionCVTutorials, Workshopshttps://cvpr.thecvf.com/ACORE2021
ICMR: ACM International Conference on Multimedia RetrievalCV, IR/Mining, NLP, Signal http://icmr2024.org/BCORE2021
Advanced Concepts for Intelligent Vision SystemsCV  BCORE2021
ICIP: International Conference on Image ProcessingCVDemo, SpecialSession, Tutorials, Workshopshttps://2024.ieeeicip.org/BCORE2021
Image and Vision Computing ConferenceCV  BCORE2021
ACCV: Asian Conference on Computer VisionCVDemo, StudentThesis / Doctor symposium, Tutorials, Workshopshttps://accv2024.org/BCORE2021
FG : IEEE International Conference on Automatic Face & Gesture RecognitionCV https://fg2024.ieee-biometrics.org/CCORE2021
International Conference on Control, Automation, Robotics and VisionCV, Specific  CCORE2021
International Conference on Computer Vision SystemsCVTutorials, Workshops CCORE2021
International Conference on Machine VisionCVSpecialSession CCORE2021
BMVC: British Machine Vision ConferenceCVWorkshops --
MLMI : International Workshop on Machine Learning in Medical ImagingCV  --
3DV : International Conference on 3D VisionCVDemo, Tutorialshttps://3dvconf.github.io/2024/--
ISBI : IEEE International Symposium on Biomedical ImagingCV, SpecificSpecialSession, Tutorialshttps://biomedicalimaging.org/2024/--
International Conference on Computer Vision and GraphicsCV  --
International Machine Vision and Image Processing ConferenceCVWorkshops --
Machine Vision ApplicationsCV  --
International Conferences in Central Europe on Computer Graphics, Visualization and Computer VisionCV  --
NeurIPS: Neural Information Processing SystemsML/CSBestPaperAward, Demo, Industrial, StudentPaper, Tutorials, Workshopshttps://nips.cc/Conferences/2023ACORE2021
IJCAI: International Joint Conference on Artificial IntelligenceML/CS https://ijcai24.org/ACORE2021
ECMLPKDD: European Conference on Machine learning and knowledge discovery in databasesIR/Mining, ML/CSTutorials, Workshopshttps://2024.ecmlpkdd.org/ACORE2021
ICML: International Conference on Machine LearningML/CS https://icml.cc/Conferences/2024ACORE2021
PAKDD: Pacific-Asia Conference on Knowledge Discovery and Data MiningIR/Mining, ML/CSTBAhttps://pakdd2024.org/ACORE2021
SIGKDD : ACM SIGKDD International Conference on Knowledge discovery and data miningIR/Mining, ML/CS https://kdd.org/kdd2024/ACORE2021
LAK : International Conference on Learning Analytics And KnowledgeIR/Mining, ML/CSStudentThesis / Doctor symposiumhttps://www.solaresearch.org/events/lak/lak24/ACORE2021
ICLR: International Conference on Learning RepresentationsML/CSTBAhttps://iclr.cc/Conferences/2024ACORE2021
ICDE : International Conference on Data Engineering WorkshopsML/CS https://icde2024.github.io/ACORE2021
CIKM: ACM International Conference on Information and Knowledge ManagementIR/Mining, ML/CS https://www.cikm2024.org/ACORE2021
European Conference on Artificial IntelligenceML/CSTutorials, Workshopshttps://www.ecai2024.eu/ACORE2021
IEEE International Conference on Data Science and Advanced AnalyticsML/CSTutorialshttps://conferences.sigappfr.org/dsaa2023/ACORE2021
AISTATS: International Conference on Artificial Intelligence and StatisticsML/CS https://aistats.org/aistats2024/ACORE2021
LICS : IEEE Symposium on Logic in Computer ScienceML/CS, Specific https://lics.siglog.org/lics24/ACORE2021
CIDR : Conference on Innovative Data Systems ResearchML/CS http://www.cidrdb.org/cidr2024/index.htmlACORE2021
SDM : SIAM International Conference on Data Mining (SDM)ML/CS https://www.siam.org/conferences/cm/conference/sdm24ACORE2021
KR: International Conference on Principles of Knowledge Representation and ReasoningIR/Mining, ML/CSStudentThesis / Doctor symposium, Tutorials, Workshopshttps://kr.org/KR2024/ACORE2021
SODA : ACM SIAM Symposium on Discrete AlgorithmsML/CS https://www.siam.org/conferences/cm/conference/soda24ACORE2021
ICDMW : IEEE International Conference on Data MiningML/CSTutorials, Workshopshttps://www.cloud-conf.net/icdm2023/ACORE2021
UAI: Conference on Uncertainty in Artificial IntelligenceML/CS https://www.auai.org/uai2024/ACORE2021
Logics in Artificial Intelligence, European ConferenceML/CS, Specific  ACORE2021
COLT: Conference on Learning TheoryML/CS https://learningtheory.org/colt2024/ACORE2021
SIGMOD : ACM SIGMOD International Conference on Management of DataML/CSTBAhttps://2024.sigmod.org/ACORE2021
STOC : ACM Symposium on Theory of ComputingML/CS, Specific http://acm-stoc.org/stoc2024/ACORE2021
AAAI: Association for the Advancement of Artificial IntelligenceML/CS https://aaai.org/aaai-conference/ACORE2021
International Conference on Artificial Intelligence in EducationML/CS, Specific https://www.aied2023.org/ACORE2021
ICPR : International Conference on Pattern RecognitionML/CS http://www.icprs.org/BCORE2021
FUZZ : IEEE International Conference on Fuzzy SystemsML/CS  BCORE2021
International Conference on Tools with Artificial IntelligenceML/CS  BCORE2021
Australasian Joint Conference on Artificial IntelligenceML/CSTutorials, Workshops BCORE2021
Educational Data MiningIR/Mining, ML/CS, Specific https://educationaldatamining.org/edm2024/BCORE2021
International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming for Combinatorial Optimization ProblemsML/CS https://sites.google.com/view/cpaior2024BCORE2021
Big Data : IEEE International Conference on Big DataIR/Mining, ML/CSSpecialSession, Tutorials, Workshopshttps://bigdataieee.org/BigData2024/BCORE2021
DCC : Data Compression ConferenceML/CS, Specific https://www.cs.brandeis.edu/~dcc/index.htmlBCORE2021
International Conference on Scientific and Statistical Data Base ManagementML/CS https://ssdbm.org/2024/BCORE2021
Web and Big DataIR/Mining, ML/CSWorkshops BCORE2021
Pacific Rim International Conference on Artificial IntelligenceML/CSTutorials, Workshops BCORE2021
IFIP WG 11.3 Working Conference on Data and Applications Security (also known as DBSEC)ML/CS, Specific  BCORE2021
Australian Data Mining ConferenceIR/Mining, ML/CSStudentThesis / Doctor symposium, Tutorials, Workshops BCORE2021
SAC : ACM Symposium on Applied ComputingML/CS http://www.sigapp.org/sac/sac2024/BCORE2021
International Conference on Agents and Artificial IntelligenceML/CSDemo, Panel, SpecialSession, StudentThesis / Doctor symposium, Tutorials, Workshopshttps://icaart.scitevents.org/BCORE2021
Artificial Intelligence in Medicine in EuropeML/CS, Specific https://www.aimedicine.info/aime24/BCORE2021
European Symposium on Artificial Neural NetworksML/CS https://www.esann.org/BCORE2021
SMC : IEEE International Conference on Systems, Man and CyberneticsML/CSTutorials, Workshopshttps://ieeesmc2024.org/BCORE2021
International Conference on Modelling Decisions for Artificial IntelligenceML/CS http://www.mdai.cat/mdai2024/BCORE2021
International Conference on Neural Information ProcessingML/CSTutorials, Workshops BCORE2021
Intelligent Data AnalysisML/CS https://ida2024.org/BCORE2021
IV : IEEE Intelligent Vehicles SymposiumML/CS, Specific https://2024.ieee-iv.org/BCORE2021
IJCNN: International Joint Conference on Neural NetworksML/CS  BCORE2021
Data Warehousing and Knowledge DiscoveryIR/Mining, ML/CSWorkshopshttps://www.dexa.org/dawak2024BCORE2021
CEC : IEEE Congress on Evolutionary ComputationML/CS, Specific  BCORE2021
ISIT : IEEE International Symposium on Information TheoryML/CS https://2024.ieee-isit.org/homeBCORE2021
International Conference on Intelligent Data Engineering and Automated LearningML/CS, SpecificSpecialSessionhttps://ideal2023.uevora.pt/CCORE2021
EUROML/CS https://euro2024cph.dk/CCORE2021
Artificial Intelligence Applications and InnovationsML/CS https://ifipaiai.org/CCORE2021
International Symposium on Artificial Life and RoboticsML/CS https://isarob.org/symposium/CCORE2021
International FLINS Conference on Robotics and Artificial Intelligence (was International Fuzzy Logic and Intelligent technologies in Nuclear Science Conference)ML/CS  CCORE2021
International Conference on Engineering Applications of Neural NetworksML/CS https://eannconf.org/2024/CCORE2021
IEEE/ACM International Conference on Big Data Computing, Applications and TechnologiesML/CSWorkshopshttps://bdcat-conference.org/CCORE2021
IEEE Symposium on Computational Intelligence and Data MiningML/CSWorkshops CCORE2021
International Conference on Internet of Things, Big Data and SecurityML/CSDemo, Panel, SpecialSession, Tutorials, Workshopshttps://iotbds.scitevents.org/CCORE2021
International Symposium on Neural NetworksML/CS https://conference.cs.cityu.edu.hk/isnn/CCORE2021
FUSION : International Conference on Information FusionML/CS  CCORE2021
International Conference on Machine Learning and ApplicationsML/CSSpecialSessionhttps://www.icmla-conference.org/icmla24/CCORE2021
International Cross-Domain Conference for Machine Learning and Knowledge ExtractionIR/Mining, ML/CS, NLPSpecialSession CCORE2021
ICANN: International Conference on Artificial Neural NetworksML/CS https://e-nns.org/icann2024/CCORE2021
International Conference on Artificial Intelligence and LawML/CS, Specific  CCORE2021
International Conference on Data Science, Technology and ApplicationsML/CSTBAhttps://data.scitevents.org/CCORE2021
International Conference on the Statistical Analysis of Textual DataML/CS, NLP  CCORE2021
International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed ComputingML/CSSpecialSession, Workshopshttps://acisinternational.org/conferences/snpd-2024/CCORE2021
International Conference on Model and Data EngineeringML/CSWorkshops CCORE2021
IEEE International Symposium on Artificial LifeML/CS, Specific  CCORE2021
International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert SystemsML/CS  CCORE2021
FRUCTML/CSPostershttps://www.fruct.org/conferences/35/call-for-participation/--
MMPR/IOIML/CS  --
AISTCV, IR/Mining, ML/CS, NLP https://aistconf.org/--
L@S : ACM Conference on Learning @ ScaleML/CS https://learningatscale.hosting.acm.org/las2024/--
International Work-Conference on Artificial and Natural Neural NetworksML/CS  --
International Symposium on Artificial Intelligence and MathematicsML/CS https://isaim2024.cs.ou.edu/--
MIPT conferenceML/CS https://conf.mipt.ru/--
SGAI International Conference on Artificial IntelligenceML/CS  --
International Conference on Hybrid Artificial Intelligence SystemsML/CS  --
International Conference on Artificial Intelligence: Methodology, Systems, ApplicationsML/CS  --
IEEE International Conference on Data Science and EngineeringML/CS  --
Portuguese Conference on Artificial IntelligenceML/CSStudentThesis / Doctor symposium --
LomonosovML/CS https://lomonosov-msu.ru/eng/event/9000/--
International Conference on Machine Learning and CyberneticsML/CS https://www.icmlc.com/--
Conference on Visualization and Data AnalysisCV, ML/CS  --
AutoMLML/CSTutorials, Workshopshttps://2024.automl.cc/--
International Conference on Distributed Computing and Artificial IntelligenceML/CS  --
Florida Artificial Intelligence Research Society ConferenceML/CS https://www.flairs-37.info/--
International Work-conference on the Interplay between Natural and Artificial ComputationML/CS  --
International Conference on Artificial IntelligenceML/CS  --
GECCO: Genetic and Evolutionary Computation ConferenceML/CS, Specific https://gecco-2024.sigevo.org/HomePage--
Language, Data and KnowledgeIR/Mining, ML/CS, NLPPosters, Tutorials, Workshops --
Asian Conference on Machine LearningML/CSWorkshops --
AIES : AAAI/ACM Conference on AI, Ethics, and SocietyML/CS, Specific  --
International Conference on Artificial Intelligence and Soft ComputingML/CS https://icaisc.eu/--
+ +

Journals

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Journal nameCategoryImpactURL
Foundations and Trends in Machine LearningML38.78https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=34
International Journal of Information ManagementML21.35https://robotics.sciencemag.org/
Science RoboticsML, Specific17.02https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=9670
IEEE Transactions on Pattern Analysis and Machine IntelligenceCV, Comp. Math, ML15.84https://www.journals.elsevier.com/signal-processing
Nature Machine IntelligenceML13.63https://www.frontiersin.org/journals/robotics-and-ai
Artificial Intelligence ReviewML, NLP11.67https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6570654
IEEE Transactions on Neural Networks and Learning SystemsML10.47https://www.osapublishing.org/josaa/home.cfm
IEEE Transactions on Fuzzy SystemsComp. Math, ML10.12https://www.springer.com/journal/521
ACM Transactions on Intelligent Systems and TechnologyML9.9https://www.springer.com/journal/11721
Neural NetworksML9.7https://www.journals.elsevier.com/neurocomputing
Expert Systems with ApplicationsML9.6https://www.springer.com/journal/12559
International Journal of Intelligent SystemsML9.34https://www.comsoc.org/publications/journals/ieee-tccn
Soft RoboticsML, Specific9.22http://www.jmlr.org/
Journal of Intelligent ManufacturingML9.18https://www.journals.elsevier.com/international-journal-of-information-management/
CAAI Transactions on Intelligence TechnologyML9.11???
Knowledge-Based SystemsML8.66https://www.sciencedirect.com/journal/pattern-recognition
Engineering Applications of Artificial IntelligenceML8.64https://www.journals.elsevier.com/digital-signal-processing
Pattern RecognitionCV, ML, NLP, Signal8.54https://www.springer.com/journal/11548
Advanced Engineering InformaticsML8.53https://link.springer.com/journal/10845
Information SciencesML8.51https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6221037
Artificial Intelligence in MedicineML, Specific8.3https://www.journals.elsevier.com/neural-networks
IEEE/CAA Journal of Automatica SinicaML7.7https://onlinelibrary.wiley.com/journal/14680394
International Journal of Robotics ResearchML, Specific7.38https://onlinelibrary.wiley.com/journal/1098111x
IEEE Transactions on Cognitive Communications and NetworkingML7.12https://www.journals.elsevier.com/fuzzy-sets-and-systems
NeurocomputingML6.19https://www.springer.com/journal/10115
Fuzzy Optimization and Decision MakingML6.06http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=91
Cognitive Systems ResearchML5.99https://www.springer.com/journal/10951
Minds and MachinesML5.92https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7274989
IEEE Intelligent SystemsML5.82http://www.elsevier.com/wps/find/journaldescription.cws_home/505651/description#description
IEEE Computational Intelligence MagazineML5.71https://www.mdpi.com/journal/jimaging
Pattern Recognition LettersCV, ML, NLP, Signal5.67https://www.springer.com/journal/10700
Computational LinguisticsML, NLP5.63http://journals.cambridge.org/action/displayJournal?jid=NLE
Neural Computing and ApplicationsML5.6https://www.journals.elsevier.com/journal-of-memory-and-language
Artificial IntelligenceML, NLP5.57https://www.sciencedirect.com/journal/medical-image-analysis
Applied IntelligenceML5.44https://www.journals.elsevier.com/knowledge-based-systems
Integrated Computer-Aided EngineeringComp. Math, ML5.44http://online.liebertpub.com/soro
Journal of Machine Learning ResearchML5.41https://journals.sagepub.com/home/ijr
Journal of Parallel and Distributed ComputingML, Specific5.27https://www.tandfonline.com/toc/teta20/current
Progress in Artificial IntelligenceML5.2https://www.springer.com/journal/10339
Artificial Intelligence and LawML, Specific4.94https://www.springer.com/journal/10851
Fuzzy Sets and SystemsML4.76https://www.journals.elsevier.com/artificial-intelligence/
ACM Transactions on Human-Robot InteractionML4.69???
International Journal of Machine Learning and CyberneticsCV, ML4.66https://www.iospress.nl/journal/integrated-computer-aided-engineering/
Journal of Artificial Intelligence and Soft Computing ResearchCV, ML4.62https://www.tandfonline.com/toc/hscc20/current
IEEE Transactions on Human-Machine SystemsML, Signal4.6https://www.journals.elsevier.com/engineering-applications-of-artificial-intelligence
Machine LearningML4.54https://dl.acm.org/journal/tcps
Design StudiesML, Specific4.36https://www.springer.com/journal/41315
International Journal of Approximate ReasoningML, Specific4.31https://www.hindawi.com/journals/acisc/
International Journal of Fuzzy SystemsComp. Math, ML4.23https://www.journals.elsevier.com/advanced-engineering-informatics
Frontiers in NeuroroboticsML, Specific4.08http://www.springer.com/computer+science/ai/journal/10489
Applied Computational Intelligence and Soft ComputingML4.07https://journals.sagepub.com/home/arx
Network NeuroscienceML4.07https://www.springer.com/journal/11067
Autonomous RobotsML, Specific3.94https://www.springer.com/journal/10032
Big Data and Cognitive ComputingML3.9https://www.springer.com/journal/498
Journal of Intelligent and Robotic Systems: Theory and ApplicationsML, Specific3.61https://www.springer.com/journal/10601
Journal of Artificial Intelligence ResearchML3.59https://www.journals.elsevier.com/expert-systems-with-applications
Frontiers in Robotics and AIML3.47???
IEEE Transactions on Cognitive and Developmental SystemsML3.45https://onlinelibrary.wiley.com/journal/17568765
RoboticsML, Specific3.4https://dl.acm.org/journal/jacm
Autonomous Agents and Multi-Agent SystemsML3.38???
Swarm IntelligenceML, Specific3.31https://www.journals.elsevier.com/information-sciences
Intelligent Service RoboticsML, Specific3.15https://www.mitpressjournals.org/netn
Digital Signal Processing: A Review JournalComp. Math, ML, Signal3.15http://jaiscr.eu/
Expert SystemsComp. Math, ML3.09https://www.jair.org/index.php/jair
ACM Transactions on Cyber-Physical SystemsML3.08http://www.springer.com/computer+science/ai/journal/11063
Knowledge and Information SystemsML3.06https://link.springer.com/journal/11263
Computational IntelligenceComp. Math, ML3.02https://www.springer.com/journal/10458
Evolutionary IntelligenceML2.96https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5962385
Journal of Intelligent Information SystemsML2.94https://www.mitpressjournals.org/loi/coli
Applied Artificial IntelligenceML2.92http://www.computability.de/journal/
AI and SocietyML2.87https://www.iospress.nl/journal/argument-computation/
Journal of the ACMML2.87https://www.journals.elsevier.com/design-studies
AI MagazineML2.87https://www.springer.com/journal/10844
Journal of Experimental and Theoretical Artificial IntelligenceML2.85https://www.springer.com/journal/10732
Systems Science and Control EngineeringML2.8http://www.actapress.com/Content_of_Journal.aspx?JournalID=119
Neural Processing LettersML2.8https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4200690
Topics in Cognitive ScienceML2.74https://www.cambridge.org/core/journals/theory-and-practice-of-logic-programming
Applied System InnovationML, Specific2.73https://www.journals.elsevier.com/physics-of-life-reviews
IET Cyber-Physical Systems: Theory and ApplicationsML2.72https://www.springer.com/journal/10590
ACM Transactions on Interactive Intelligent SystemsML2.47https://www.springer.com/journal/11023
Networks and Spatial EconomicsML, Specific2.4https://www.springer.com/journal/10846
Knowledge Engineering ReviewML2.39https://www.springer.com/journal/11370
Physics of Life ReviewsComp. Math, ML, Specific2.38https://www.nowpublishers.com/MAL
KybernetesML2.38http://ijfs.usb.ac.ir/
Cognitive ScienceML2.35https://www.emerald.com/insight/publication/issn/0368-492X
Argument and ComputationComp. Math, ML2.28https://www.iospress.nl/journal/international-journal-of-knowledge-based-and-intelligent-engineering-systems/
Cybernetics and SystemsML2.24https://www.mdpi.com/journal/robotics
Iranian Journal of Fuzzy SystemsML, Specific2.24https://www.sciencedirect.com/journal/journal-of-parallel-and-distributed-computing
Journal of HeuristicsML2.24https://www.springer.com/journal/10994
Journal of SchedulingML2.2http://journals.cambridge.org/action/displayJournal?jid=KER
IEEE Transactions on GamesML, Specific2.18https://onlinelibrary.wiley.com/journal/14678640
Journal of Intelligent SystemsML2.16https://www.springer.com/journal/146
International Journal of Advanced Robotic SystemsML2.15https://www.springer.com/journal/10817
Machine TranslationML, NLP2.15???
Journal of PragmaticsML2.11https://www.tandfonline.com/toc/uaai20/current
Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAMML2.04http://www.ijfis.org/main.html
Natural Language EngineeringML, NLP2.03https://onlinelibrary.wiley.com/journal/15516709
Spatial Information ResearchML2???
Journal of Intelligent and Fuzzy SystemsML, Specific1.95https://www.tandfonline.com/toc/ucbs20/current
KI - Kunstliche IntelligenzML1.91https://www.degruyter.com/view/journals/jisys/jisys-overview.xml
International Journal of Swarm Intelligence ResearchML1.86https://academic.oup.com/jos
International Journal of Intelligent Robotics and ApplicationsML1.81https://dl.acm.org/journal/tiis
Theory and Practice of Logic ProgrammingComp. Math, ML1.73https://aaai.org/Magazine/magazine.php
International Journal of Knowledge and Systems ScienceML1.69https://www.tandfonline.com/loi/lnfa20
Journal on Data SemanticsCV, ML, NLP, Signal1.68http://www.nnw.cz/
International Journal of Pattern Recognition and Artificial IntelligenceCV, ML1.67https://www.worldscientific.com/worldscinet/ijait
Journal of Automated ReasoningComp. Math, ML, Specific1.66https://www.journals.elsevier.com/cognitive-systems-research
Bulletin of the Polish Academy of Sciences: Technical SciencesML1.66https://www.journals.elsevier.com/journal-of-pragmatics
International Journal of Humanoid RoboticsML, Specific1.6https://www.worldscientific.com/worldscinet/ijprai
Neural Network WorldML1.57https://www.fujipress.jp/jaciii/jc/
Cognitive ProcessingML1.45https://www.worldscientific.com/worldscinet/ijufks
Adaptive BehaviorML1.44https://www.worldscientific.com/worldscinet/ijhr
AI CommunicationsML1.37http://journals.pan.pl/dlibra/journal/119067
International Journal of Software InnovationML1.34https://journal.iberamia.org/index.php/intartif/index
International Journal on Artificial Intelligence ToolsML1.33https://www.worldscientific.com/worldscinet/ijseke
International Journal of Fuzzy Logic and Intelligent SystemsML1.31http://www.springer.com/computer+science/ai/journal/10472
International Journal of Software Engineering and Knowledge EngineeringML1.31https://www.aicommunications.eu/
Intelligent Data AnalysisCV, ML1.3https://www.tandfonline.com/loi/tfie20
Annals of Mathematics and Artificial IntelligenceComp. Math, ML1.3https://journals.sagepub.com/home/adb
International Journal of Robotics and AutomationML, Specific1.25https://www.iospress.nl/journal/intelligent-data-analysis/
Informatica (Slovenia)ML1.21https://www.worldscientific.com/worldscinet/ijsc
International Journal of Cognitive Informatics and Natural IntelligenceML1.19???
Parallel ComputingML1.16???
International Journal of Uncertainty, Fuzziness and Knowlege-Based SystemsML1.15https://www.journals.elsevier.com/parallel-computing
Intelligenza ArtificialeML1.13https://www.kybernetika.cz/
Journal of SemanticsML1.12https://constructivist.info/
Inteligencia ArtificialML0.95https://www.igi-global.com/journal/international-journal-swarm-intelligence-research/1149
Web IntelligenceML0.95https://www.springer.com/journal/10015
Automatic Control and Computer SciencesComp. Math, ML0.93https://digital-library.theiet.org/content/journals/iet-spr
ConstraintsComp. Math, ML0.88https://www.iospress.nl/journal/journal-of-intelligent-fuzzy-systems/
IEICE Transactions on Information and SystemsML0.88https://journals.agh.edu.pl/csci
International Journal of Semantic ComputingML0.84https://www.jstage.jst.go.jp/browse/transinf
Artificial Life and RoboticsML0.84https://www.iospress.nl/journal/intelligenza-artificiale/
Computer ScienceML0.83https://www.iospress.nl/journal/web-intelligence-and-agent-systems/
International Journal of Knowledge-Based and Intelligent Engineering SystemsML0.81http://journals.cambridge.org/action/displayJournal?jid=AIE
KybernetikaML0.8http://cogsci.snu.ac.kr/jcs/
ComputabilityComp. Math, ML0.71https://www.springer.com/computer/database+management+%26+information+retrieval/journal/13740
Journal of Advanced Computational Intelligence and Intelligent InformaticsML0.53https://www.igi-global.com/journal/international-journal-software-innovation/64245
Journal of Robotics, Networking and Artificial LifeML0.49???
Fuzzy Information and EngineeringML0.45http://www.informatica.si/index.php/informatica
Computer Science Journal of MoldovaML0.43https://www.igi-global.com/journal/international-journal-knowledge-systems-science/1169
Journal of Cognitive ScienceML0.39https://www.igi-global.com/journal/international-journal-cognitive-informatics-natural/1095
Constructivist FoundationsML0.36https://www.tandfonline.com/action/journalInformation?journalCode=tssc20
Medical Image AnalysisCV, Specific15.24https://www.journals.elsevier.com/journal-of-visual-communication-and-image-representation
International Journal of Computer VisionCV, ML11.81https://www.journals.elsevier.com/pattern-recognition-letters
Computerized Medical Imaging and GraphicsCV8.4https://www.springer.com/journal/12065
IEEE Transactions on Visualization and Computer GraphicsCV, Signal5.56https://www.frontiersin.org/journals/neurorobotics
Cognitive ComputationCV5.24https://www.springer.com/journal/40815
International Journal on Document Analysis and RecognitionCV, NLP4.4https://onlinelibrary.wiley.com/journal/10981098
Signal Processing: Image CommunicationCV, Signal3.97http://computeroptics.smr.ru/eng/index.html
International journal of computer assisted radiology and surgeryCV3.77https://digital-library.theiet.org/content/journals/iet-cvi
Journal of Visual Communication and Image RepresentationCV, Signal3.5https://www.springer.com/journal/10506
Journal of ImagingCV3.43???
Computer OpticsCV3.26https://www.springer.com/journal/13042
Information VisualizationCV3.23https://journals.sagepub.com/home/ivi
Machine Vision and ApplicationsCV3.05https://www.journals.elsevier.com/international-journal-of-approximate-reasoning
International Journal of Imaging Systems and TechnologyCV2.88https://www.journals.elsevier.com/speech-communication
Pattern Analysis and ApplicationsCV, ML2.76https://www.springer.com/journal/13748
Journal of the Optical Society of America A: Optics and Image Science, and VisionCV2.25https://www.springer.com/journal/10462
Spatial Cognition and ComputationCV1.88https://www.journals.elsevier.com/computers-and-graphics
Computers and GraphicsCV, Signal1.88https://www.journals.elsevier.com/artificial-intelligence-in-medicine
Journal of Mathematical Imaging and VisionCV, Comp. Math1.67https://www.springer.com/journal/10514
IET Computer VisionCV1.64https://tist.acm.org/
Pattern Recognition and Image AnalysisCV, ML1.24https://www.springer.com/journal/11493
Imaging Science JournalCV1.17https://www.tandfonline.com/loi/yims20
Journal of Computer and Systems Sciences InternationalCV, ML1.04https://www.springer.com/journal/11488
International Journal of Image and GraphicsCV0.92https://www.worldscientific.com/worldscinet/ijig
Intelligent Decision TechnologiesCV, ML0.74https://www.iospress.nl/journal/intelligent-decision-technologies/
Information FusionSignal18.92https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=79
IEEE Signal Processing MagazineSignal9.72https://iopscience.iop.org/journal/0266-5611
Mechanical Systems and Signal ProcessingSignal9.09https://benjamins.com/catalog/ijcl
IEEE Journal on Selected Topics in Signal ProcessingSignal8.93https://www.springer.com/computer/journal/11714?detailsPage=aboutThis
IEEE Transactions on MultimediaSignal7.27https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6570655
IEEE/ACM Transactions on Audio Speech and Language ProcessingComp. Math, Signal6.02https://tsas.acm.org/
Computer Vision and Image UnderstandingCV, Signal5.53https://www.journals.elsevier.com/mathematics-and-computers-in-simulation
IEEE Transactions on Signal ProcessingSignal5.27https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=97
Signal ProcessingCV, Signal4.99https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=2945
Image and Vision ComputingCV, Signal4.63https://www.springer.com/journal/40998
Journal of the Franklin InstituteSignal4.48https://ieeexplore.ieee.org/xpl/aboutJournal.jsp?punumber=6884276
APSIPA Transactions on Signal and Information ProcessingSignal4.3https://www.ipol.im/
IEEE Transactions on Parallel and Distributed SystemsComp. Math, Signal4.3https://onlinelibrary.wiley.com/journal/10991115
IEEE Transactions on Control of Network SystemsSignal3.77https://www.springer.com/journal/11760
IEEE Signal Processing LettersSignal3.67https://jivp-eurasipjournals.springeropen.com
IEEE Transactions on Signal and Information Processing over NetworksSignal3.59http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=71
International Journal of Adaptive Control and Signal ProcessingSignal3.54https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=78
Electronics (Switzerland)Signal3.27https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=93
Eurasip Journal on Image and Video ProcessingSignal3.24https://www.sciencedirect.com/journal/information-fusion
Frontiers of Information Technology and Electronic EngineeringSignal3.05https://www.nowpublishers.com/SIG
Foundations and Trends in Signal ProcessingSignal3https://www.mdpi.com/journal/electronics
Circuits, Systems, and Signal ProcessingComp. Math, Signal2.72https://www.springer.com/journal/11128
Multidimensional Systems and Signal ProcessingComp. Math, ML, Signal2.37https://www.springer.com/journal/34
IEEE MultimediaSignal2.26https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6046
Iranian Journal of Science and Technology - Transactions of Electrical EngineeringSignal2.25https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4149689
ACM Transactions on Spatial Algorithms and SystemsSignal2.23https://www.springer.com/journal/11045
IET Image ProcessingCV, Signal2.2https://www.sciencedirect.com/journal/computer-vision-and-image-understanding
Eurasip Journal on Advances in Signal ProcessingSignal2.1https://www.cambridge.org/core/journals/apsipa-transactions-on-signal-and-information-processing
IET Signal ProcessingSignal1.99http://ieee-iotj.org/
Signal, Image and Video ProcessingSignal1.97https://www.sciencedirect.com/journal/journal-of-the-franklin-institute
Quantum Information ProcessingSignal, Specific1.91https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6509490
Journal of Signal Processing SystemsSignal1.87https://www.journals.elsevier.com/information-processing-letters
Mathematics of Control, Signals, and SystemsComp. Math, Signal1.61https://www.tandfonline.com/loi/tinf20
Numerical Functional Analysis and OptimizationComp. Math, Signal1.43https://www.igi-global.com/journal/international-journal-computer-assisted-language/41023
Image Processing On LineCV, Signal1.39https://www.springer.com/journal/11265
INFORSignal1.27https://asp-eurasipjournals.springeropen.com/
Information Processing LettersSignal1.14https://www.journals.elsevier.com/image-and-vision-computing
Computer Assisted Language LearningNLP5.74https://www.springer.com/journal/10579
Language Learning and TechnologyNLP4.57https://www.iospress.nl/journal/applied-ontology/
ReCALLNLP4.43https://www.lltjournal.org//
Journal of Memory and LanguageML, NLP4.07https://www.journals.elsevier.com/computerized-medical-imaging-and-graphics
Speech CommunicationNLP4https://ieeexplore.ieee.org/xpl/aboutJournal.jsp?punumber=10207
Language Resources and EvaluationNLP2.15http://www.degruyter.de/journals/cllt/detailEn.cfm
Corpus Linguistics and Linguistic TheoryNLP1.98http://www.elsevier.com/wps/find/journaldescription.cws_home/622902/description#description
International Journal of Speech TechnologyCV, NLP, Signal1.94https://www.cambridge.org/core/journals/recall
Applied OntologyNLP1.71https://www.tandfonline.com/toc/ncal20/current
International Journal of Computer-Assisted Language Learning and TeachingNLP, Specific1.44https://www.worldscientific.com/worldscinet/ijsc
International Journal of Corpus LinguisticsNLP1.13https://www.springer.com/journal/10772
International Journal of Semantic ComputingNLP0.84https://www.tandfonline.com/loi/nmcm20
IEEE Internet of Things JournalCV, ML, Signal, Specific10.98???
IEEE Transactions on Evolutionary ComputationComp. Math15.5https://www.springer.com/journal/12351/
Applied and Computational MathematicsComp. Math9.25https://www.worldscientific.com/worldscinet/aa
Archives of Computational Methods in EngineeringComp. Math9.18https://www.ams.org/publications/journals/journalsframework/tran
Journal of Computational Design and EngineeringComp. Math6.57https://www.ams.org/publications/journals/journalsframework/mcom
IEEE Transactions on Knowledge and Data EngineeringComp. Math6.09https://www.journals.elsevier.com/computational-statistics-and-data-analysis
Applied Mathematical ModellingComp. Math5.44https://www.journals.elsevier.com/journal-of-informetrics
SIAM ReviewComp. Math4.86https://www.springer.com/journal/10588
International Journal of Artificial Intelligence in EducationComp. Math4.82http://www.ijfis.org/main.html
Journal of Numerical MathematicsComp. Math4.76https://link.springer.com/journal/40304
Technology, Knowledge and LearningComp. Math4.44http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4235
Applied Mathematics and ComputationComp. Math4.36https://www.springer.com/journal/10208
International Journal of Automation and ComputingComp. Math4.28https://www.iospress.nl/journal/informatica/
Applied Mathematics LettersComp. Math4.22https://www.springer.com/journal/245
Journal of InformetricsComp. Math4.2https://www.ams.org/publications/journals/journalsframework/bull
Evolutionary ComputationComp. Math4.14https://www.inderscience.com/jhome.php?jcode=ijcsm
InformaticaComp. Math3.91https://www.ems-ph.org/journals/journal.php?jrn=jems
Mathematics and Computers in SimulationComp. Math3.81https://www.worldscientific.com/worldscinet/m3as
EPJ Data ScienceComp. Math3.78https://www.siam.org/publications/journals/siam-review-sirev
Mathematical Models and Methods in Applied SciencesComp. Math3.78https://www.springer.com/mathematics/journal/40687
Intelligent Automation and Soft ComputingComp. Math3.54https://www.springer.com/journal/450
IEEE Transactions on ComputersComp. Math3.19https://www.springer.com/journal/607
Foundations of Computational MathematicsComp. Math3.12https://www.siam.org/publications/journals/siam-journal-on-scientific-computing-sisc
Computers and Mathematics with ApplicationsComp. Math3.11https://www.tandfonline.com/toc/gcom20/current
Computational and Applied MathematicsComp. Math3.09https://www.siam.org/publications/journals/siam-journal-on-numerical-analysis-sinum
Computational and Mathematical Organization TheoryComp. Math3.06https://www.tandfonline.com/toc/tsma20/current
Computational and Mathematical Methods in MedicineComp. Math3https://www.journals.elsevier.com/journal-of-combinatorial-theory-series-a
Operational ResearchComp. Math2.97https://www.journals.elsevier.com/journal-of-logical-and-algebraic-methods-in-programming
Journal of the American Mathematical SocietyComp. Math2.95https://www.springer.com/journal/11633
International Journal of Computers, Communications and ControlComp. Math2.92https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7756
Computing (Vienna/New York)Comp. Math2.91https://academic.oup.com/imaiai
Journal of Computational and Applied MathematicsComp. Math2.87https://academic.oup.com/imajna
Applied Numerical MathematicsComp. Math2.87https://www.journals.elsevier.com/information-and-computation
ACM Transactions on Mathematical SoftwareComp. Math2.79https://www.mdpi.com/journal/computation
Journal of Organizational Computing and Electronic CommerceComp. Math2.76https://www.springer.com/journal/11390
SIAM Journal of Scientific ComputingComp. Math2.72https://www.springer.com/journal/180
Information and InferenceComp. Math2.69https://www.springer.com/journal/10915
SIAM Journal on Numerical AnalysisComp. Math2.69https://www.atlantis-press.com/journals/ijcis
International Journal of Computational Intelligence SystemsComp. Math2.62https://www.springer.com/journal/10589
Journal of Scientific ComputingComp. Math2.62https://www.emerald.com/insight/publication/issn/0264-4401
ComputationComp. Math2.55https://www.journals.elsevier.com/applied-mathematics-letters
International Journal of Data Science and AnalyticsComp. Math2.52https://www.springer.com/journal/10044
Journal of the Brazilian Society of Mechanical Sciences and EngineeringComp. Math2.44https://www.inderscience.com/jhome.php?jcode=ijmic
Bayesian AnalysisComp. Math, ML2.42https://www.ams.org/publications/journals/journalsframework/jams
Revista de la Real Academia de Ciencias Exactas, Fisicas y Naturales - Serie A: MatematicasComp. Math2.42https://journals.sagepub.com/home/act
AlgorithmsComp. Math2.36http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=69
Journal of Strain Analysis for Engineering DesignComp. Math2.33https://www.springer.com/journal/10
Methods, Data, AnalysesComp. Math2.3https://www.springer.com/journal/11950
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Journal of the European Mathematical SocietyComp. Math2.29https://www.siam.org/publications/journals/siam-journal-on-applied-mathematics-siap
International Journal of Intelligent Transportation Systems ResearchComp. Math2.27https://academic.oup.com/jssam
International Journal of Applied Mathematics and Computer ScienceComp. Math2.25https://www.global-sci.org/aamm.html
Applied Mathematics and OptimizationComp. Math2.23???
Statistics and ComputingComp. Math2.22https://www.techscience.com/journal/iasc
Numerische MathematikComp. Math2.22https://www.springer.com/journal/12190
Advances in Data Analysis and ClassificationComp. Math2.22https://www.springer.com/journal/10231
Inverse ProblemsComp. Math, Signal2.22https://www.journals.elsevier.com/mechanical-systems-and-signal-processing/
Measurement Science and TechnologyComp. Math2.21https://www.springer.com/journal/10255
Studies in Applied MathematicsComp. Math2.2https://www.journals.elsevier.com/applied-mathematical-modelling
Optimal Control Applications and MethodsComp. Math2.19http://acmij.az/view.php?lang=en&menu=0
International Journal of Nonlinear Sciences and Numerical SimulationComp. Math2.18https://www.anstuocmath.ro/
Journal of Computer Science and TechnologyComp. Math2.18https://www.springer.com/journal/40593
Concurrency Computation Practice and ExperienceComp. Math2.18https://www.journals.elsevier.com/journal-of-complexity
OptimizationComp. Math2.17https://www.springer.com/journal/11083
IEEE Journal on Multiscale and Multiphysics Computational TechniquesComp. Math2.15https://msp.org/jomms/about/journal/research.html
IMA Journal of Numerical AnalysisComp. Math2.14https://dl.acm.org/journal/tocl
Electrical EngineeringComp. Math2.12https://www.cambridge.org/core/journals/combinatorics-probability-and-computing
Software-Intensive Cyber-Physical SystemsComp. Math2.11http://univagora.ro/jour/index.php/ijccc/
Journal of Nonlinear and Variational AnalysisComp. Math2.07https://www.springer.com/journal/10878
ACM Transactions on Parallel ComputingComp. Math2.05http://mia.ele-math.com/
Smart ScienceComp. Math2https://www.cambridge.org/core/journals/numerical-mathematics-theory-methods-and-applications
Advances in Computational MathematicsComp. Math2https://www.mitpressjournals.org/loi/evco
Journal of Survey Statistics and MethodologyComp. Math1.97https://www.tandfonline.com/toc/gapa20/current
Measurement and ControlComp. Math1.97https://www.springer.com/journal/894
Distributed ComputingComp. Math1.96https://www.tandfonline.com/toc/hoce20/current
Computational Statistics and Data AnalysisComp. Math1.96https://www.springer.com/journal/11222
Journal of Molecular ModelingComp. Math1.95https://www.journals.elsevier.com/advances-in-applied-mathematics
SIAM Journal on Mathematical AnalysisComp. Math1.94https://www.inderscience.com/jhome.php?jcode=ijcse
ESAIM: Mathematical Modelling and Numerical AnalysisComp. Math1.94https://www.springer.com/journal/365
SIAM Journal on Applied MathematicsComp. Math1.93https://dl.acm.org/journal/toms
Computational Optimization and ApplicationsComp. Math1.92https://www.esaim-m2an.org/
Bulletin of Mathematical BiologyComp. Math1.91http://www.societyforchaostheory.org/ndpls/
Mathematics of ComputationComp. Math1.9https://www.esaim-cocv.org/
East Asian Journal on Applied MathematicsComp. Math1.89https://www.journals.elsevier.com/operations-research-letters
Inverse Problems in Science and EngineeringComp. Math1.88https://iopscience.iop.org/journal/0957-0233
Analysis and ApplicationsComp. Math1.88https://projecteuclid.org/euclid.ba
Advances in Calculus of VariationsComp. Math1.84https://www.springer.com/journal/10623
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Advances in Fuzzy SystemsComp. Math1.78https://www.springer.com/journal/40314
Bulletin of the American Mathematical SocietyComp. Math1.76http://www.springer.com/engineering/journal/11831
Engineering ComputationsComp. Math1.74https://www.journals.elsevier.com/journal-of-computer-and-system-sciences
Journal of Mechanics of Materials and StructuresComp. Math1.74https://www.springer.com/journal/40315
Journal of Mathematical BehaviorComp. Math1.7https://www.journals.elsevier.com/journal-of-combinatorial-theory-series-b
Nonlinear Analysis, Theory, Methods and ApplicationsComp. Math1.7https://www.tandfonline.com/toc/gscs20/current
Optimization Methods and SoftwareComp. Math1.69https://www.cambridge.org/core/journals/advances-in-applied-probability
Communications in Contemporary MathematicsComp. Math1.66https://www.springer.com/journal/10114
Computational Thermal SciencesComp. Math1.66https://www.aimsciences.org/journal/1078-0947
International Journal of Computer MathematicsComp. Math1.63???
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IEEE Pervasive ComputingComp. Math1.58https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=12
Journal of Inverse and Ill-Posed ProblemsComp. Math1.57https://www.amcs.uz.zgora.pl/
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Advances in Computational DesignComp. Math1.57https://www.journals.elsevier.com/applied-mathematics-and-computation
IMA Journal of Management MathematicsComp. Math1.56https://www.springer.com/journal/453
International Journal of Computational MethodsComp. Math1.54https://epjdatascience.springeropen.com/
Computational StatisticsComp. Math1.53https://www.degruyter.com/view/journals/jnma/jnma-overview.xml
Stochastic Processes and their ApplicationsComp. Math1.51https://journals.sagepub.com/home/sdj
Discrete OptimizationComp. Math1.49https://www.springer.com/journal/13348
Constructive ApproximationComp. Math1.49https://www.degruyter.com/view/journals/cmam/cmam-overview.xml
IMA Journal of Mathematical Control and InformationComp. Math1.48http://www.informaworld.com/smpp/title~content=t713640037~db=all
Discrete and Continuous Dynamical SystemsComp. Math1.47https://www.journals.elsevier.com/journal-of-mathematical-analysis-and-applications
Stochastic Analysis and ApplicationsComp. Math1.46https://www.tandfonline.com/loi/uspp20
ESAIM - Control, Optimisation and Calculus of VariationsComp. Math1.45https://www.springer.com/journal/10444
Fundamenta InformaticaeComp. Math1.44https://www.springer.com/journal/446
Designs, Codes, and CryptographyComp. Math1.44https://academic.oup.com/imaman
International Journal of Innovative Computing, Information and ControlComp. Math1.43https://www.sciencedirect.com/journal/nonlinear-analysis
Journal of Combinatorial OptimizationComp. Math1.42http://www.aimsciences.org/journal/2155-3289
Applicable Analysis and Discrete MathematicsComp. Math1.4https://www.springer.com/journal/40430
Acta Applicandae MathematicaeComp. Math1.4https://msp.org/camcos/2019/14-2/
Lifetime Data AnalysisComp. Math1.39http://www.aftabi.com/DIE/die.html
Journal of Combinatorial Theory. Series BComp. Math1.39https://www.journals.elsevier.com/discrete-applied-mathematics
Integral Transforms and Special FunctionsComp. Math1.39https://www.hindawi.com/journals/cmmm/
Statistics and Public PolicyComp. Math1.39https://www.springer.com/journal/11538
Journal of Mathematical Analysis and ApplicationsComp. Math1.38https://dl.acm.org/journal/topc
Journal of Statistical Computation and SimulationComp. Math1.38https://www.worldscientific.com/worldscinet/ijwmip
Computational Methods in Applied MathematicsComp. Math1.37https://www.springer.com/journal/211
International Journal of Wavelets, Multiresolution and Information ProcessingComp. Math1.37https://www.combinatorics.org/ojs/index.php/eljc
Advances in Mathematical PhysicsComp. Math1.36https://www.global-sci.org/eajam.html
Differential and Integral EquationsComp. Math1.36???
Zeitschrift fur Analysis und ihre AnwendungComp. Math1.36https://www.intlpress.com/site/pub/pages/journals/items/cms/_home/_main/index.php
Results in MathematicsComp. Math1.35https://www.ejgta.org/index.php/ejgta/index
ACM Transactions on Computational LogicComp. Math1.35https://www.worldscientific.com/worldscinet/ijcm
Transactions of the American Mathematical SocietyComp. Math1.34http://www3.interscience.wiley.com/journal/2133/home
International Journal of Computational Science and EngineeringComp. Math1.33https://www.cambridge.org/core/journals/forum-of-mathematics-sigma
Journal of Combinatorial Theory - Series AComp. Math1.32https://journals.sagepub.com/home/mac
AlgorithmicaComp. Math1.31https://www.tandfonline.com/toc/tmes20/current
International Journal of Fuzzy Logic and Intelligent SystemsComp. Math1.31https://www.worldscientific.com/worldscinet/nmnc
Discrete Applied MathematicsComp. Math1.31https://www.degruyter.com/view/journals/jiip/jiip-overview.xml
Mathematical and Computer Modelling of Dynamical SystemsComp. Math1.29https://www.springer.com/journal/25
Journal of Pseudo-Differential Operators and ApplicationsComp. Math1.29https://academic.oup.com/imamci/
Journal of Computer and System SciencesComp. Math1.29https://dl.acm.org/journal/toct
Collectanea MathematicaComp. Math1.28https://www.aimsciences.org/journal/1930-5311
EURO Journal on Computational OptimizationComp. Math1.28http://www.techno-press.org/?journal=acd&subpage=5
Ricerche di MatematicaComp. Math1.28https://www.springer.com/journal/11587
Networks and Heterogeneous MediaComp. Math1.27https://www.springer.com/journal/11868
AStA Advances in Statistical AnalysisComp. Math1.27https://www.aimsciences.org/journal/1930-5346
Operations Research LettersComp. Math1.25https://www.journals.elsevier.com/discrete-optimization
Journal of Logical and Algebraic Methods in ProgrammingComp. Math1.25https://www.mdpi.com/journal/algorithms
Evolution Equations and Control TheoryComp. Math1.24https://onlinelibrary.wiley.com/journal/15320634
Journal of Theoretical and Computational AcousticsComp. Math1.24https://www.mathos.unios.hr/mc/index.php/mc
Theory of ComputingComp. Math1.23https://www.worldscientific.com/worldscinet/jtca
Numerical Algebra, Control and OptimizationComp. Math1.22https://www.sciencedirect.com/journal/the-journal-of-mathematical-behavior
Numerical MathematicsComp. Math1.2https://www.siam.org/publications/journals/siam-journal-on-mathematical-analysis-sima
Random Structures and AlgorithmsComp. Math1.2https://www.springer.com/journal/11134
Journal of Difference Equations and ApplicationsComp. Math1.19http://jnva.biemdas.com/
Mathematical Control and Related FieldsComp. Math1.17https://www.springer.com/journal/30
Eurasian Journal of Mathematical and Computer ApplicationsComp. Math1.17http://www.informaworld.com/smpp/title~content=t713646500~db=all
Differential Equations and Dynamical SystemsComp. Math1.14https://onlinelibrary.wiley.com/journal/10982418
Advances in Differential EquationsComp. Math1.13http://caim.simai.eu/index.php/caim/index
Advances in Applied ProbabilityComp. Math1.13https://academic.oup.com/imamat
Nonlinear Dynamics, Psychology, and Life SciencesComp. Math1.13https://onlinelibrary.wiley.com/journal/14679892
Annali di Matematica Pura ed ApplicataComp. Math1.13https://www.springer.com/journal/200
Forum of Mathematics, SigmaComp. Math1.12https://academic.oup.com/jcde
Journal of Statistical Planning and InferenceComp. Math1.12https://theoryofcomputing.org/
Applicable AnalysisComp. Math1.11https://www.journals.elsevier.com/journal-of-approximation-theory
Advances in Applied MathematicsComp. Math1.1https://www.springer.com/journal/454
Nonlinear Differential Equations and ApplicationsComp. Math1.09https://www.degruyter.com/view/j/demo
International Journal of Mathematical Education in Science and TechnologyComp. Math1.08https://www.springer.com/journal/224
Journal of Approximation TheoryComp. Math1.08https://www.aimsciences.org/journal/2156-8472
Journal of Time Series AnalysisComp. Math1.07https://journals.math.tku.edu.tw/index.php/TKJM
Journal of Algorithms and Computational TechnologyComp. Math1.07https://link.springer.com/journal/13675
Communications in Mathematical Biology and NeuroscienceComp. Math1.05https://www.tandfonline.com/toc/gipe20/current
Communications in Mathematical SciencesComp. Math1.05https://www.journals.elsevier.com/stochastic-processes-and-their-applications
New Mathematics and Natural ComputationComp. Math1.04https://www.springer.com/education+%26+language/learning+%26+instruction/journal/10758
International Journal of Grid and Utility ComputingComp. Math1.04https://academic.oup.com/qjmam
Quarterly of Applied MathematicsComp. Math1.03https://www.aimsciences.org/journal/1556-1801
Advances in Applied Mathematics and MechanicsComp. Math1.03https://www.worldscientific.com/worldscinet/ccm
Quarterly Journal of Mechanics and Applied MathematicsComp. Math1.02https://www.ams.org/publications/journals/journalsframework/proc
Information and ComputationComp. Math1.01https://www.iospress.nl/journal/fundamenta-informaticae/
Journal of Symbolic ComputationComp. Math1.01https://www.journals.elsevier.com/journal-of-computational-and-applied-mathematics
Analele Stiintifice ale Universitatii Ovidius Constanta, Seria MatematicaComp. Math1.01https://www.hindawi.com/journals/amp/
Aequationes MathematicaeComp. Math1.01https://www.degruyter.com/view/j/form
Advances in Mathematics of CommunicationsComp. Math1.01https://www.degruyter.com/view/j/agms
Computational Methods and Function TheoryComp. Math1.01http://ejmca.enu.kz/
Communications in Applied Mathematics and Computational ScienceComp. Math1https://www.ams.org/publications/journals/journalsframework/qam
Analysis and Geometry in Metric SpacesComp. Math1https://ieee-jmmct.org/
Mathematical Inequalities and ApplicationsComp. Math1https://www.inderscience.com/jhome.php?jcode=ijguc
Queueing SystemsComp. Math1https://www.springer.com/journal/11786
IMA Journal of Applied MathematicsComp. Math0.99http://www.aftabi.com/ADE/ade.html
Journal of Computational MathematicsComp. Math0.98https://www.journals.elsevier.com/journal-of-statistical-planning-and-inference
Tamkang Journal of MathematicsComp. Math0.98https://www.springer.com/journal/10182
Forum MathematicumComp. Math0.97http://www.springer.com/engineering/electronics/journal/202
Proceedings of the American Mathematical SocietyComp. Math0.96https://www.springer.com/journal/12591
Vestnik Sankt-Peterburgskogo Universiteta, Prikladnaya Matematika, Informatika, Protsessy UpravleniyaComp. Math0.95https://mda.gesis.org/index.php/mda/index
Mathematical CommunicationsComp. Math0.95https://onlinelibrary.wiley.com/journal/15214001
European Journal of Applied MathematicsComp. Math0.94https://www.tandfonline.com/toc/lsaa20/current
Qualitative Theory of Dynamical SystemsComp. Math0.92https://www.springer.com/journal/10985
European Journal of CombinatoricsComp. Math0.92https://www.tandfonline.com/toc/goms20/current
Communications in Applied and Industrial MathematicsComp. Math0.92https://www.cambridge.org/core/journals/european-journal-of-applied-mathematics
Discrete and Computational GeometryComp. Math0.89https://www.journals.elsevier.com/european-journal-of-combinatorics
ACM Transactions on Computation TheoryComp. Math0.88https://www.journals.elsevier.com/computers-and-mathematics-with-applications
Combinatorics Probability and ComputingComp. Math0.87https://www.tandfonline.com/toc/hmes20/current
Computing and InformaticsComp. Math0.87http://www.compama.co.usb.ve/
International Journal of Computing Science and MathematicsComp. Math0.86http://www.hindawi.com/journals/afs/
Theory of Computing SystemsComp. Math0.84https://www.ems-ph.org/journals/journal.php?jrn=zaa
Bulletin of the South Ural State University, Series: Mathematical Modelling, Programming and Computer SoftwareComp. Math0.83http://www.apmath.spbu.ru/ru/resource/vestnik/
Applied MathematicsComp. Math0.8https://www.degruyter.com/view/j/jaa?lang=en
International Journal of Modelling, Identification and ControlComp. Math0.8https://www.springer.com/journal/10440
Acta Mathematica Sinica, English SeriesComp. Math0.8https://www.springer.com/engineering/electronics/journal/13177
Applied Mathematics E - NotesComp. Math0.79https://mmp.susu.ru/page/en/greet
Bulletin of Computational Applied MathematicsComp. Math0.78http://www.math.nthu.edu.tw/~amen/
OrderComp. Math0.76https://www.begellhouse.com/journals/computational-thermal-sciences.html
Communications in Mathematics and StatisticsComp. Math0.73https://www.journals.elsevier.com/applied-numerical-mathematics/
Applicable Algebra in Engineering, Communications and ComputingComp. Math0.72???
Journal of Modern DynamicsComp. Math0.68https://www.springer.com/journal/12346
Journal of Applied AnalysisComp. Math0.67http://www.cai.sk/ojs/index.php/cai
Electronic Journal of Graph Theory and ApplicationsComp. Math0.66https://mcfns.net/index.php/Journal
Electronic Journal of CombinatoricsComp. Math0.63???
Acta Mathematicae Applicatae SinicaComp. Math0.62https://www.degruyter.com/view/journals/acv/acv-overview.xml
Mathematics in Computer ScienceComp. Math0.54https://www.springer.com/journal/11634
Dependence ModelingComp. Math0.52https://www.aimsciences.org/journal/A0000-0000
Journal of Computational Methods in Sciences and EngineeringComp. Math0.48https://www.springer.com/journal/11766
Mathematical and Computational Forestry and Natural-Resource SciencesComp. Math0.47https://www.degruyter.com/view/journals/ijnsns/ijnsns-overview.xml
Journal of Applied Mathematics and InformaticsComp. Math0.47https://www.iospress.nl/journal/journal-of-computational-methods-in-sciences-and-engineering/
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+ + diff --git a/ru/materials/nir/index.html b/ru/materials/nir/index.html new file mode 100644 index 00000000..187be6e2 --- /dev/null +++ b/ru/materials/nir/index.html @@ -0,0 +1,2262 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Отчеты НИР + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
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+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + +

2024 FALL

+ +

Postgraduate Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + +
Postgraduate studentYearPhD thesis topicScientific adviserLink to publication
Viktor Pankratov2Probabilistic topic modelingVorontsov K.V.Paper,Code,Slides
Konstantin Yakovlev1Tensor Methods in Federated LearningGasnikov A.V.Publication 1, Publication 2
+ +

Second Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Galina Boeva2Efficient aggregation by labels for the problem of event sequencesZaytsev A. A.Publication, Paper, Slides, Code
Nikita Kornilov2Optimal Flow Matching: Learning Straight Trajectroies in Just One StepGasnikov A.V.Publication, Paper, Slides, Code
+ +

First Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearTopicScientific adviserLink to publication
Nikita Kiselev1Unraveling the Hessian: A Key to Smooth Convergence in Loss Function LandscapesGrabovoy A.V.Paper, Code, Slides
Daniil Dorin1Декодирование визуальных стимулов из мультимодальных сигналов мозгаGrabovoy A.V.Publication, Paper1, Paper2, Code1, code2, Slides
Kirill Semkin1Time series classification in parameters space using NeuralODEStrijov V.V.Paper,Code,Slides,
Andrey Veprikov1The optimal control problem in artificial intelligence systems with feedback loopKhritankov A.S.Paper, Code,Slides
Ilgam Latypov1γ-Competitiveness: An Approach to Multi-Objective Optimization with High Computation Costs in Lipschitz FunctionsDorn Y.V.Paper, Code, Slides
Ignashin Igor1Stochastic Correspondences Frank-WolfeGrabovoy A.V.Paper, Code, Slides
+ +

Fourth Year Bachelor Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Papay Ivan4Ordinal Classification Using Partially Ordered Feature SetsStrijov V.V.Code Paper Slides
Meshkov Vladislav4ConvNets Landscape Convergence: Hessian-Based Analysis of Matricized NetworksGrabovoy A.V.Paper, Code, Slides
Stepanov Ilia4The use of synthetic data obtained using a generative neural network to improve the quality of detection modelsGrabovoy A.V.Paper, Code, Slides
Nabiev Muhammadsharif4Inductive Bias in Model SelectionBakhteev O. Y.Paper, Code, Slides
Zadvornov Egor4Forecasting social trends with high volatilityMalkov A. S.Paper, Code, Slides
Rebrikov Aleksei4Investigation of Neural Network Sparsification Mechanisms Based on Weight ImportanceBeznosikov A.N.Paper, Code, Slides
Firsov Sergey4Neural architecture search with target hardware controlBakhteev O. Y.Paper, Code, Slides
+ +

2024 SPRING

+

Postgraduate Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Postgraduate studentYearPhD thesis topicScientific adviserLink to publication
Vasiliy Alekseev4Incompleteness and Instability of Topic ModelsVorontsov K.V.Paper1, Paper2, Paper3; Slides1, Slides2
Novitskii Vasilii3New Bounds for One-point Oracle in Stochastic Gradient-free OptimizationGasnikov A.V.Paper 1, Paper 2, Paper 3, Slides, Code, Text
Alexey Grishanov2Applying Reinforcement Learning for Recommendation Platform PersonalizationVorontsov K.V.Paper 1, Paper 2, Code, Slides
Panchenko Sviatoslav2Graph diffusion models for the task of brain signal decodingStrijov V.V.Code, Slides, Paper1
Pavel Severilov2Decoding of multimodal signals of brain activityStrijov V.V.Paper1 Paper2 Thesis, Code, Slides Paper1
Denis Tikhonov2Attractor reconstruction for linearized system with miltilinear mapStrijov V.V.Code, Slides Paper1
Viktor Pankratov1Probabilistic topic modelingVorontsov K.V.Paper,Code,Slides
+ +

Second Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Klypa Roman2Generative modeling for protein structure and interactionsGrudinin S.V.Paper, Slides, Code
Kovaleva Maria2Addition of external information for enhancement of local embeddings for event sequences data modelsZaytsev A. A.Paper, Thesis, Slides, Code
Ksenofontov Gregory2Adversarial Schrödinger BridgesRoman IsachenkoCode, Slides, Draft, Draft
Konstantin Yakovlev2Concordant Neural Architecture Search on Multidomain DataBakhteev O. Y.Paper, Slides, Code
Tolmachev Alexander2Information Bottleneck Analysis of Deep Neural NetworksAlexey FrolovPaper, Paper2, Slides
Polina Barabanshchikova2Tverberg type theoremsPolyanskii A.A.Draft, Slides, Code
Alkin Emil2Expressive Power of Recurrent Neural Networks, IIIvan OseledetsDraft, Slides, Code
+ +

First Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Boeva Galina1Label Attention Network for Temporal Sets predictionZaytsev A. A.Full Paper Paper, Slides, Code
Chumachenko Arina1Machine learning methods for functional brain mappingSharaev M. G.Paper, Slides, Code
Marat Khusainov1Adaptive sampling methods using diffusion modelsSamsonov S.V.Paper, Slides , Code
Kornilov Nikita1Optimal Flow MatchingGasnikov A.V.Paper, Slides, Code
Kseniia Petrushina1Quantifying image realism via language model reasoningsAlexander PanchenkoPaper, Slides , Code
Parviz Karimov1Representation learning for collections of dataIsachenko R.V.Paper, Slides, Code
Dmitry Protasov1Automatic Music TranscriptionIvan MatveevPaper, Slides, Code
German Gritsai1Automatic Detection of Machine Generated TextsGrabovoy A. V.Paper 1, Paper 2, Slides
+ +

Fourth Year Bachelor Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Nikita Kiselev4Bayesian Sample Size EstimationGrabovoy A. V.Thesis, Paper 1, Code 1, Paper 2, Code 2, Slides
Andrey Veprikov4A Mathematical Model of the Hidden Feedback Loop Effect in Machine Learning SystemsKhritankov A.S.Paper, Code, Slides
Ilgam Latypov4Balancing Efficiency and Interpretability: A New Approach to Multi-Objective Optimization with High Computation Costs in Lipschitz FunctionsDorn Y.V.Paper, Code, Slides
Anna Remizova4reducing the dimension of the space of the trainable parameters in the domain adaptation problemGrabovoy A. V.Paper, Code, Slides
Anastasia Voznyuk4Detection of machine-generated fragments based on text style change analysisGrabovoy A. V.Paper, Code, Slides
Dorin Daniil4Spatial-temporal characteristics in the time series decodingGrabovoy A. V.Paper 1, Code 1, Paper 2, Code 2, Slides
Semkin Kirill4Tensor decomposition and forecast for multidimensional time seriesStrijov V.V.Paper, Code, Slides
Nikitina Maria4Analysis of distribution bias in contrastive learningIsachenko R.V.Paper, Code, Slides
Babkin Petr4Differential Neural Ensemble Search with Diversity ControlBakhteev O.Yu.Paper, Code, Slides
Ignashin Igor4Bayesian distillation of transformer-based modelsGrabovoy A. V.Paper, Code, Slides
Terentyev Alexander4Classification of trajectories of dynamic systems using physically-informed neural networksStrijov V.V.Paper, Code, Slides
Matvei Kreinin4Methods with preconditioning and weight decayingBeznosikov A.N.Paper, Code, Slides
Alexander Bogdanov4Application of zero-order stochastic approximation with memoization technique in the Frank-Wolfe algorithmBeznosikov A.N.Paper, Code, Slides
Okhotnikov Nikita4Interconnected latent representations for outfit generation taskIsachenko R.V.Paper, Code, Slides
Oleinik Mikhail4Knowledge distillation in deep neural networks using model structure alignment methodsBakhteev O.Y.Paper, Code, Slides
+ +

2023 FALL

+ +

Postgraduate Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Postgraduate studentYearPhD thesis topicScientific adviserLink to publication
Viktor Pankratov1Probabilistic topic modelingVorontsov K.V.Paper,Code,Slides
Pavel Severilov2Decoding of multimodal signals of brain activityStrijov V.V.Paper, Code, Slides
Alexey Grishanov2Applying Reinforcement Learning for Recommendation Platform PersonalizationVorontsov K.V.Paper 1, Paper 2 - under review, Code, Slides
Novitskii Vasilii3New Bounds for One-point Oracle in Stochastic Gradient-free OptimizationGasnikov A.V.Paper 1, Paper 2, Paper 3, Slides, Code
Vasiliy Alekseev4Incompleteness and Instability of Topic ModelsVorontsov K.V.Conf1 (Slides1), Slides2
Tikhonov Denis2Dimensionality reduction of tensor phase spaces in nonlinear dynamical system reconstructionStrijov V.V.(Slides), Code
Panchenko Sviatoslav2Graph Diffusion models for human brain activity decodingStrijov V.V.Paper, Slides, Code
+ +

Second Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Rustem Islamov2Distributed Newton-Type Methods with Communication Compression and Bernoulli AggregationStrijov V.V., Richtarik P.Paper, Code, Slides
Kovaleva Maria2Addition of global information for enhancement of local embeddings for transactional data modelsZaytsev A.APaper, Slides
Tolmachev Alexander2Information Bottleneck Analysis of Deep Neural NetworksAlexey FrolovPaper, Slides
Klypa Roman2Generative modeling for protein structure and interactionsGrudinin S.V.Slides, Code
Polina Barabanshchikova2Tverberg type theoremsPolyanskii A.A.Paper, Slides
Konstantin Yakovlev2Concordant Neural Architecture Search on Multidomain DataBakhteev O. Y.Paper, Slides, Code
Ksenofontov Gregory2Adversarial Schrödinger BridgesRoman IsachenkoCode, Slides, Draft
Alkin Emil2Expressive Power of Recurrent Neural Networks, IIIvan OseledetsDraft, Slides, Code
+ +

First Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearTopicScientific adviserLink to publication 
Yakovlev Konstantin1Concordant Neural Architecture Search on Multidomain DataBakhteev O. Y.Paper, Code, Slides 
Galina Boeva1Identifying the relationship between labels using an attention-based algorithm for the Next Basket Recommendation taskZaytsev A.APaper Code Slides 
Bair Mikhailov1Undersampled MRI ReconstructionDylov D.VSlides 
Pavel Bartenev1MRI data augmentation via conditional generative 3D inpaintingMaxim SharaevSlides Code 
Kseniia Petrushina1Detection of hallucinations of language modelsAlexander PanchenkoSlides Code 
Arina Chumachenko1Machine learning methods for functional brain mappingMaxim SharaevSlidesCode
Nikita Kornilov1Intermediate Gradients Methods with Relative InexactnessAlexandr GasnikovSlides Code Paper 
Dmitry Protasov1Automatic Music TranscriptionIvan MatveevSlides Code Draft 
Parviz Karimov1Representation learning for data point groupsRoman IsachenkoSlides Draft 
Eduard Vladimirov1Adversarial attacks on neural networks for time seriesZaytsev A.ASlides Code Draft 
Zharov Georgiy1Search for an effective architecture for solving the problem of obtaining multimodal embeddings for three or more modalities Slides Code 
+ +

Fourth Year Bachelor Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Antyshev Tikhon4Gradient Sliding for Saddle Point problems with one compositeGasnikov A. V.Code Paper Slides
Kiselev Nikita4Bayesian Sample Size EstimationGrabovoy A. V.Paper, Code, Slides
Kreinin Matvei4On methods with preconditioning and weight decayingBeznosikov A. N.Paper, Code, Slides
Ilgam Latypov4Research On multicriteria optimization using Shapley ValueDorn Y.V.Paper, Code, Slides
Anastasiia Vozniuk4Detection of Machine-Generated Fragments in TextGrabovoy A.V.Paper, Code, Slides
Terentyev Alexander4Classification of trajectories of dynamic systems with physics-informed neural networksStrijov V.V.Paper, Code, Slides
Veprikov Andrey4A mathematical model of the hidden feedback loop effects in machine learning systemsKhritankov A.S.Paper, Code, Slides
Ignashin Igor4Bayesian distilation of transformer-based modelsGrabovoy A.V.Paper, Code, Slides
Remizova Anna4Altering latent representation in the audio style transfer taskGrabovoy A.V.Paper, Code, Slides, Paper handwritten draft
Babkin Petr4Differential neural ensemble search with diversity controlBakhteev O.Y.Paper, Code, Slides
Nikitina Maria4Analysis of distribution bias in contrastive learningIsachenko R.V.Paper, Code, Slides
Oleinik Mikhail4Knowledge distillation in deep neural networks using model structure alignment methodsBakhteev O.Y.Paper, Code, Slides
Semkin Kirill4Tensor-SSA method in application to time series decompositionStrijov V.V.Paper, Code, Slides
Bogdanov Alexander4New Aspects of Black Box Conditional Gradient: Variance Reduction and One Point FeedbackBeznosikov A. N.Paper, Code, Slides
Dorin Daniil4Spatial-temporal characteristics in the time series decodingGrabovoy A. V.Paper, Code, Slides
Okhotnikov Nikita4Interconnected latent representations for outfit generation taskIsachenko R.V.Paper, Code, Slides
+ +

2023 SPRING

+ +

Postgraduate Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Postgraduate studentYearPhD thesis topicScientific adviserLink to publication
Pavel Severilov1Decoding of multimodal signals of brain activityStrijov V.V.Code, Slides
Grishanov Alexey1Applying Reinforcement Learning for Recommendation Platform PersonalizationVorontsov K.V.Paper, Code, Slides
Panchenko Sviatoslav1Graph Diffusion Models for the Task of Signal DecodingStrijov V.V.Paper (Translated, draft), Code, Slides (IDP conf.)
Vasilii Novitskii2New Bounds for One-point Oracle in Stochastic Gradient-free OptimizationGasnikov A.V.Paper 1, Paper 2, Slides, Code
Alina Samokhina2Continous-in-time representations of signalsStrijov V.V.Code old, Paper draft, Slides
Vasiliy Alekseev3Incompleteness and Instability of Topic ModelsVorontsov K.V.Paper (draft), Slides
Aleksei Goncharov4Space-time series alignment modelsStrijov V.V.Papers, Slides, Thesis
Petr Ostroukhov4Tensor Methods for Convex Functions MinimizationGasnikov A.V.Paper, Slides
Denis Kuznetsov4Neural network models of dialogue on general topicsBurtsev M.S.Paper with Code
Radoslav Neychev4Informative prior in privileged learningStrijov V.V.Old paper, Paper 1, New paper 2 (in blind review for now)
+ +

Second Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Rustem Islamov2Distributed Newton-Type Methods with Communication Compression and Bernoulli AggregationStrijov V.V., Richtarik P.Paper, Code, Slides
Filatov Andrei2Text interfaces for event sequencesStrijov V.V.Paper, Slides
Shokorov Viacheslav2Bootstrapping of neural network ensemblesVetrov D.P.Text (draft) Slides, Code
Safiullin Robert2Multimodel representation of dynamic systemsStrijov V.V.Paper Slides, Code
Bishuk Anton2Controlled Graph GenerationZukhba A.V.Paper, Code, Slides
Pankratov Viktor2Probabilistic topic modelingVorontsov K.V.Paper, Code, Slides
Grebenkova Olga2Automatic detection of focal cortical dysplasia for sparse data representationBurnaev EDraft, Code, Slides Paper
Nadezhda Alsahanova2Selection of tensor representations for multiview forecastingStrijov V.V.Draft, Code, Slides
+ +

First Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearTopicScientific adviserLink to publication
Yakovlev Konstantin1Concordant Neural Architecture Search on Multidomain DataBakhteev O. Y.Paper, Code, Slides
Kovaleva Maria1Neural architecture search with early stoppingAlexey ZaytsevCode, Slides, Draft
Ksenofontov Gregory1Analysis of generative modeling methods based on Schrödinger bridgesRoman IsachenkoCode, Slides, Draft
Polina Barabanshchikova1Helly type problems for d-intervalsPolyanskii A.A.Paper, Slides
Tolmachev Alexander1Information Bottleneck Analysis of Deep Neural NetworksAlexey FrolovPaper, Slides
Alkin Emil1Expessive Power of Recurrent Neural NetworksOseledets I. V.Slides, Code
+ +

Fourth Year Bachelor Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Antyshev Tikhon4Gradient Sliding for Saddle Point problems with one compositeGasnikov A. V.Code Paper Slides
Kornilov Nikita4Gradient Free Methods for Non-Smooth Convex Stochastic Optimization with Heavy Tails on Convex CompactGasnikov A. V.Code Paper Slides
Lukyanenko Ivan4Detection of manipulations and its targets in news textsVorontsov K.V.Code, Text, Slides
Zharov Georgiy4Classification of manipulative fragments in news textsVorontsov K.V.Code, Slides
Vladimirov Eduard4Choosing a state space model in a neural decoding problemStrijov V.V.Code1, Code2, Slides
Molozhavenko Alexander4Solution of a block multidimensional eigenvalues search problemGasnikov A.V.Slides, Code
+ +

2022 AUTUMN

+ +

Postgraduate Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Postgraduate studentYearPhD thesis topicScientific adviserLink to publication
Vasiliy Alekseev3Incompleteness and Instability of Topic ModelsVorontsov K.V.Paper, Paper (conf.)
Grishanov Alexey1Applying Reinforcement Learning for Recommendation Platform PersonalizationVorontsov K.V.Paper, Code, Slides (Sber AI Lab seminar)
Panchenko Sviatoslav1Graph Diffusion Models for the Task of Signal DecodingStrijov V.V.Paper (Article, draft), Code, Slides (IDP conf.)
Denis1Dimension reduction of tensor phase spaces in dynamical system simulationStrijov V.V.Paper, Code, Slides
Alina Samokhina2Continous-in-time representations of signalsStrijov V.V.Code old, Paper published, Paper draft, Slides
Vasilii Novitskii2New Bounds for One-point Oracle in Stochastic Gradient-free OptimizationGasnikov A.V.Paper 1, Paper 2, Slides, Code
Polina Potapova3Topic modeling for multilingual topic searchVorontsov K.V.Paper, Code
     
+ +

Second Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Andrei Filatov2Infinite transformersStrijov V.V.Paper, Code, Slides
Rustem Islamov2Distributed Newton-Type Methods with Communication Compression and Bernoulli AggregationStrijov V.V., Richtarik P.Paper, Code, Slides
Bishuk Anton2Controlled Graph GenerationZukhba A.V.Paper, Code, Slides
Grebenkova Olga2Automated detection of focal cortical dysplasiaBurnaev ESlides Acceptance letter
Safiullin Robert2Multimodel representation of dynamic systemsStrijov V.V.Paper, Code, Slides
Shokorov Viacheslav2Deep ensembles bootstrappingVetrov D.P.Notes, Code
Pankratov Viktor2Probabilistic topic modelingVorontsov K.V.Paper, Code, Slides
Alsahanova Nadezhda2Selection of tensor representations for multiview forecastingStrijov V.V.Paper, Code, Slides
+ +

First Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearTopicScientific adviserLink to publication
Maria Kovaleva1Research of efficient transformersAlexey ZaytsevPaper, Code, Slides
Roman Klypa1Combination of geometrical learning and language models for bioinformaticsGrudinin S.V.Slides
Polina Barabanshchikova1Helly type problems for d-intervalsPolyanskii A.A.Paper, Slides
Ksenofontov Gregory1Creating a personalized avatar of a person for a virtual fitting of clothesVorontsov K.V., Yanina A.O.Slides
Yakovlev Konstantin1Concordant Neural Architecture Search on multi-domain dataBakhteev O.Y.Slides
+ +

Fourth Year Bachelor Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Eduard Vladimirov4Ways to account for data noise in a Neural ODE modelStrijov V.V.Paper, Code, Slides
Antyshev Tikhon4Zero-order Mirror Descent for Saddle Point ProblemsGasnikov A.V.Paper, Code, Slides
Ivan Lukyanenko4Joint NER and RE in manipulation newsVorontsov K.V.Code Slides
Kornilov Nikita4Gradient Free Optimization with Infinite VarianceGasnikov A.V.Paper, Slides
Georgiy Zharov4Search for manipulations and their relations with named entities in textsVorontsov K.V.Slides
Molozhavenko Alexander4Solution of a block multidimensional eigenvalues search problemGasnikov A.V.Slides, Code
+ +

2022 SPRING

+ +

Postgraduate Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Postgraduate studentYearPhD thesis topicScientific adviserLink to publication
Andrey Grabovoy1Bayesian DistilationStrijov V.V.Code, Thesis
Alina Samokhina1Continous-time representation for signal decodingStrijov V.V.Code, Paper, Slides
Nikitin Filipp2Generation and selection of graph neural network models in the problem of organic chemistryStrijov V. V.Code
Polina Potapova2Topic modeling for multilingual topic searchVorontsov K.V.Paper, Code
Vasiliy Alekseev2Incompleteness and Instability of Topic ModelsVorontsov K.V.Paper (not visible), Code (private)
Ostroukhov Petr3Tensor methods for convex optimizationGasnikov A.V.Paper 1, Paper 2
Kamil Safin3Combined methods for text plagiarism detectionChehovich Y.V.Paper
Denis Kuznetsov3Neural network models of dialogue on general topicsBurtsev M.S.Paper_1, Paper_2
Ilia Zharikov4Neural network methods for document image recognitionVorontsov K.V.Paper, Code, Slides
Alex Goncharov3Space-time series alignment modelsStrijov V.V.Papers, Slides
+ +

Second Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Petr Mokrov2Wasserstein gradient flows: modeling and applicationsBurnaev E.V.Paper, Code, Slides
Denis Tikhonov2Quasiperiodic time signals classification with spherical harmonicsStrijov V.V.Paper, Code, Slides
Natalia Varenik2Building a connectivity map of functional groups in the problem of decoding brain signalsStrijov V.V.Paper, Code, Slides
Alexey Grigorev2Regularization of neural layer via construction of frame in parameter spaceGneushev A.N.Slides, Code, Paper
Kolesov Aleksandr2Adverasrial method for Transfer Learning based on Optimal TransportBakhteev O.YPaper, Code, Slides
Severilov Pavel2Choosing the optimal model in the problem of modeling dynamics of a physical system by neural networksStrijov V.V.Paper Slides Code Paper2
Panchenko Sviatoslav2Bilinearity of geometric product for the task of signal decodingStrijov V.V.Paper, Slides Code
Grishanov Alexey2Application of Reinforcement Learning for recommendation system personalizationVorontsov K.V.Paper, Slides, Сode
+ +

First Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearTopicScientific adviserLink to publication
Rustem Islamov1Basis Matters: Better Communication-Efficient Second Order Methods for Federated LearningRichtarik P., Strijov V.V.Paper, Code, Slides
Bishuk Anton1Controlled graph generation using the variational autoencoder modelZukhba A.V.Report
Grebenkova Olga1Automated detection of focal cortical dysplasiaBurnaev EReport
Filatov Andrei1Novel view synthesisLempitsky VictorSlides Code
Safiullin Robert1Multimodel representation of dynamic systemsStrijov V.V.Paper, Code, Slides
Pankratov Viktor1Topic balancing of topic modelsVorontsov K.V.Code, Slides
Shokorov Viacheslav1Bootstrapping of neural network ensemblesVetrov D.P.Report Code
+ +

Fourth Year Bachelor Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Mariya Gorpinich4Metaparameter optimization in knowledge distillationBakhteev O.Yu.Code, Slides, Paper
Vyacheslav Gorchakov4Importance Sampling Approach to Chance-Constrained DC Optimal Power FlowMaximov Y.V.Paper, Code, Slides
Antonina Kurdyukova4Dimensionality reduction of the phase space in canonical correlation analisysStrijov V.V., Isachenko R.V.Code, Slides, Paper
Anton Pilkevich4Optimization of the criterion given by the neural network model in the text detoxification taskStrijov V.V. (Popov A.S.)Code, Slides,Paper
Konstantin Yakovlev4Selection of concordant architectures with complexity controlBakhteev O.Y.Paper Code, Slides
Khristolyubov Maxim4Approximation of the phase trajectory of the time seriesStrijov V.V.Paper Code, Slides
+ +

2021 FALL

+ +

Postgraduate Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Postgraduate studentYearPhD thesis topicScientific adviserLink to publication
Andrey Grabovoy1A prior distribution of parameters in problems of choosing deep learning modelsStrijov V.V.Paper, Code, Slides
Alina Samokhina1Continuous time representation for signal decodingStrijov V.V.Paper
Tamaz Gadaev1Multilinear model choice in forecasting problemStrijov V.V.Paper
Vasilii Novitskii1New Bounds for One-point Oracle in Stochastic Gradient-free OptimizationGasnikov A.V.Paper 1, Paper 2, Slides, Code
Vasiliy Alekseev2Incompleteness and Instability of Topic ModelsVorontsov K.V.Paper, Code, Slides1, Slides2
Polina Potapova2Topic modeling for multilingual topic searchVorontsov K.V.Paper
Petr Ostroukhov3Tensor methods for optimization of convex functionsGasnikov A.V.Paper
Denis Kuznetsov3Neural network models of dialogue on general topicsBurtsev M.S.Paper
Kamil Safin3Intrinsic methods for plagiarised texts detectionChehovich Y.V.Paper
Ilia Zharikov4Neural network methods for document image recognitionVorontsov K.V.Paper
+ +

Second Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Petr Mokrov2Wasserstein gradient flows: modeling and applicationsBurnaev E.V.Paper, Code, Slides
Denis Tikhonov2Model selection for quasiperiodic time series forecastingStrijov V.V.Code, Slides
Alexey Grigorev2Regularization of neural layer via construction of frame in parameter spaceGneushev A.N.Slides, Code; Paper
Natalia Varenik2Building a connectivity map of functional groups in the problem of decoding brain signalsStrijov V.V.Paper Slides Code
Severilov Pavel2Differential analysis of phase spaces in the problem of decoding signalsStrijov V.V.Slides Code
Panchenko Sviatoslav2Bilinearity of geometric product for the task of signal decodingStrijov V.V.Slides
Grishanov Alexey2Application of Reinforcement Learning for recommendation system personalizationVorontsov K.V.Slides, Сode
Kolesov Aleksandr2Adversarial approach for transfer learningBahteev O.Yu.Paper, Slides, Сode
+ +

First Year Master Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearTopicScientific adviserLink to publication
Rustem Islamov1Second Order Methods for Federated LearningRichtarik P, Strijov V.V.Paper, Code, Slides
Grebenkova Olga1Automated detection of focal cortical dysplasiaBurnaev EPaper, Code, Slides
Safiullin Robert1Substance properties analysis based on its SERS spectraStrijov V.V.Report, Slides
Pankratov Viktor1Topic balancing of topic modelsVorontsov K.V.Report,Code
Filatov Andrei1Task DiscoveryVictor Lempitsky Strijov V.V.Report
Bishuk Anton1Controlled graph generation using the variational autoencoder modelZukhba A.V.Report
Shokorov Viacheslav1Bootstrapping of neural network ensemblesVetrov D.P.Report Code
+ +

Fourth Year Bachelor Students

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentYearThesis topicScientific adviserLink to publication
Antonina Kurdyukova4Phase detection of human motions with signals of wearable devicesStrijov V.V.Paper, Code, Slides
Anton Pilkevich4Clustering of news text messages based on polar opinionsVorontsov K.V. 
Gorpinich Mariya4Metaparameter optimization in knowledge distillationBakhteev O.Yu.Paper, Code, Slides
Vyacheslav Gorchakov4Importance Sampling Approach to Chance-Constrained DC Optimal Power FlowMaximov Y.V.Paper, Code
Konstantin Yakovlev4Selection of concordant architectures with complexity controlBakhteev O.Y.Code, Slides
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+ + diff --git a/ru/materials/paper_guidelines/index.html b/ru/materials/paper_guidelines/index.html new file mode 100644 index 00000000..aaa92df1 --- /dev/null +++ b/ru/materials/paper_guidelines/index.html @@ -0,0 +1,268 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Рекомендации по написанию ВКР и научных работ + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Интеллектуальные системы +
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Шаблоны

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Стандарты

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Рекомендации

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Куда подать статью

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+ + diff --git a/ru/materials/scholarship/index.html b/ru/materials/scholarship/index.html new file mode 100644 index 00000000..1c5f437c --- /dev/null +++ b/ru/materials/scholarship/index.html @@ -0,0 +1,269 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Стипендии + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + +

Научная академическая стипендия им. К.В. Рудакова

+ +

Стипендия поощряет студентов 2–4 курса бакалавриата и 1–2 курса магистратуры Кафедры интеллектуального анализа данных, ведущих научные-исследования в области прикладной математики: машинного обучения, анализа данных, и других разделов математики. Стипендия выплачивается ежемесячно.

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Критерии для отбора стипендиатов

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Прием заявок на стипендию

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Состав комиссии

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Представители компаний «Антиплагиат», «ПроКомплаенс», и «Форексис»

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Шаблон заявки

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ФИО студента, Средний балл в ЛК, ФИО и ученая ступень научного руководителя, Тема научной работы, Аннотация, Ожидаемый результат (желательно указать фактический результат и формальный – журнал где планируется публикация, или другой вид представления результата), Преподавание и в развитие Кафедры ИС, участие и планы, Ссылка на дополнительные материалы (если есть; например, задел по научной работе или результаты прошлого семестра)

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+ + diff --git a/ru/materials/seminars/index.html b/ru/materials/seminars/index.html new file mode 100644 index 00000000..db409692 --- /dev/null +++ b/ru/materials/seminars/index.html @@ -0,0 +1,450 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Научные семинары + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Встречи и семинары

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Встреча с Никитой Животовским, выпускником Кафедры интеллектуальных систем МФТИ, 2013

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Дата: 21.04.2022

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Гость: Никита Животовский — канд. физ.-мат. наук., выпускник кафедры 2013, исследователь Google Research, Zürich.

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Встреча с Кириллом Павловым, выпускником Кафедры интеллектуальных систем МФТИ, 2012

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Дата: 27.03.2022

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Гость: Кирилл Павлов — выпускник кафедры 2012, исследователь.

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Встреча с Романом Сологубом, выпускником Кафедры интеллектуальных систем МФТИ, 2010

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Дата: 11.03.2022

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Гость: Роман Сологуб

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Роман — канд. физ.-мат. наук., выпускник кафедры 2010, финансовый аналитик из Лондона.

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Встреча с выпускниками Кафедры интеллектуальных систем МФТИ, 2013

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Дата: 17.02.2022

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Гости: Михаил Кузнецов, Никита Ивкин

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Выпускники кафедры занимаются исследованиями в области машинного обучения и анализа данных в крупных коммерческих компаниях.

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Априорное распределение параметров в задачах выбора моделей глубокого обучения

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Дата: 24.01.2022

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Докладчик: Андрей Грабовой

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Семинар посвящен дистилляции моделей глубокого обучения. Обсуждается выравнивание структур моделей учителя и ученика. Для оптимизации параметров ученика используется байесовский вывод. В качестве примеров учителя и ученика приводятся полносвязные и рекуррентные нейросети.

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Снижение размерности пространства в задачах декодирования сигналов

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Дата: 13.12.2021

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Докладчик: Роман Исаченко

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Доклад посвящен проблеме снижения размерности пространства при решении задачи декодирования сигналов. Процесс декодирования заключается в восстановлении зависимости между двумя гетерогенными наборами данных. Особенностью рассматриваемой задачи является наличие скрытых зависимостей не только в исходных сигналах, но и в целевых. Предлагаются методы снижения размерности, позволяющие учитывать зависимости в исходном и целевом пространствах.

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Uncertainty, Out-of-distribution detection for NNs

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Дата: 8.07.2021

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Докладчик: Максим Панов

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Максим Панов (доцент Сколтеха) расскажет на семинаре что такое Uncertainty в байесовском выводе.

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Защиты диссертаций

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Роман Исаченко, Снижение размерности пространства в задачах декодирования сигналов, 2021

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Исследуется задача выбора модели при восстановлении скрытых зависимостей в исходном и в целевом пространствах. Целевая переменная – вектор, компоненты которого являются зависимыми. Гетерогенные пространства исходных и целевых переменных обладают существенно избыточной размерностью. Требуется построить модель, адекватно описывающую исходное и целевое пространства при наблюдаемой мультикорреляции в обоих пространствах. Предлагается снизить размерность путём проецирования исходных и целевых переменных в скрытое пространство. Предлагаются линейные и нелинейные методы согласования прогностических моделей в пространствах высокой размерности.

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Ссылка на диссертацию

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Олег Бахтеев, Байесовский выбор модели глубокого обучения, 2020

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В работе рассматривается задача автоматического построения моделей глубокого обучения оптимальной и субоптимальной сложности. Под сложностью модели понимается минимальная длина описания, т.е. минимальное количество информации, которое требуется для передачи информации о модели и о выборке. Вычисление минимальной длины описания модели является вычислительно сложной процедурой. В работе предлагается получение ее приближенной оценки, основанной на связи минимальной длины описания и обоснованности модели. Для получения оценки обоснованности используются вариационные методы получения оценки обоснованности, основанные на аппроксимации неизвестного апостериорного распределения другим заданным распределением. Под субоптимальной сложностью понимается вариационная оценка обоснованности модели. Одна из проблем построения моделей глубокого обучения — большое количество параметров моделей. Поэтому задача выбора моделей глубокого обучения включает в себя выбор стратегии построения модели, эффективной по вычислительным ресурсам.

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Ссылка на диссертацию

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Анастасия Мотренко, Выбор моделей прогнозирования, 2019

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Цель работы: исследование свойств и разработка новых методов выбора модели в условиях избыточного мультикоррелирующего признакового пространства. +Проблема: при решении задачи декодирования временных рядов признаковое описание обладает корреляцией сложной мультииндексной структуры. +Избыточность признакового пространства, мультикорреляция и высокая размерность приводят к завышению сложности модели и получению неустойчивых оценок параметров. +Предложен метод выбора признаков, учитывающий многоиндексное мультикоррелирующее представление данных. Метод основан на решении задачи квадратичного программирования.

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Ссылка на диссертацию

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Александр Адуенко, Выбор мультимоделей в задачах классификации, 2017

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Мультимодели используются в случае отвержения гипотезы о простоте выборки. В случае, когда важность признаков зависит от их значений, одиночная обобщенно-линейная модель не позволяет это учесть. +Мультимодели являются интерпретируемым обобщением случая одиночной модели. Они могут содержать большое число близких моделей, что ведет к низкому качеству прогноза и потере интерпретируемости. Для решения этой проблемы предложен статистический подход к сравнению моделей и основанные на нем методы прореживания мультимоделей, позволяющие получить адекватную мультимодель, содержащую попарно статистически различимые модели.

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Ссылка на диссертацию

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Арсентий Кузьмин, Иерархическая классификация коллекций документов, 2017

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Работа посвящена разработке моделей классификации коллекций документов. Коллекция имеет иерархическую структуру, заданную экспертами. Требуется построить ранжирующую модель, которая учитывает описания документов, экспертную кластеризацию и возвращает ранжированный список релевантных тем. Предлагается метрическая вероятностная модель ранжирования тематических кластеров. Используются вариационные методы оценки вероятности принадлежности документа кластеру.

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Ссылка на диссертацию

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Защиты бакалавров и магистров

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Защита бакалавров, 2022

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Студенты: Константин Яковлев, Мария Горпинич, Антонина Курдюкова, Вячеслав Горчаков, Антон Пилькевич, Максима Христолюбов

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Защита магистров, 2022

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Студенты: Петр Мокров, Наталия Вареник, Алексей Григорьев, Святослав Панченко, Павел Северилов, Денис Тихонов, Александр Колесов, Алексей Гришанов

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Защита бакалавров, 2021

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Студенты: Дмитрий Ковалев, Антон Бишук, Кирилл Вайсер, Ольга Гребенькова, Руслан Гунаев, Владимир Жолобов, Рустем Исламов, Виктор Панкратов, Николай Савельев, Андрей Филатов, Анастасия Филиппова, Александра Харь, Вячеслав Шокоров, Тагир Саттаров

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Защита магистров, 2021

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Студенты: Егор Гладин, Андрей Грабовой, Егор Кириллов, Вадим Кислинский, Евгений Козлинский, Григорий Малиновский, Егор Шульгин, Василий Новицкий, Анна Рогозина, Никита Плетнев, Алина Самохина, Тамаз Гадаев, Глеб Моргачев

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+ + diff --git a/ru/materials/thesis/index.html b/ru/materials/thesis/index.html new file mode 100644 index 00000000..26884cbc --- /dev/null +++ b/ru/materials/thesis/index.html @@ -0,0 +1,785 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Дипломы + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Интеллектуальные системы +
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+ + Machine Learning
+ + Data Analysis
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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+ + + + +

2024

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Master’s Theses

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentThesis topicScientific adviserLink to ProjectLink to PaperLink to Slides
Maria KovalevaAddition of external information for enhancement of local embeddings for event sequences data modelsZaytsev A. A.ProjectThesisSlides
Alexander TolmachevInformation Bottleneck Analysis of Deep Neural NetworksAlexey FrolovProjectThesisSlides
Emil AlkinExpressive Power of Tensor-Train Networks With Equal TT-coresIvan OseledetsProjectThesisSlides
Klypa RomanGenerative modeling for protein structuresGrudinin S.V.ProjectThesisSlides
Ksenofontov GregoryAdversarial Schrödinger bridges on domain translation problemIsachenko R.V.ProjectPaperSlides
Barabanshchikova PolinaTverberg type theoremsPolyanskii A.A.ProjectPaperSlides
Yakovlev KonstantinGeneralized Greedy Gradient-Based Hyperparameter OptimizationBakhteev O.Y.ProjectPaperSlides
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Bachelor’s Theses

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentThesis topicScientific adviserLink to ProjectLink to PaperLink to Slides
Nikita KiselevBayesian Sample Size EstimationGrabovoy A.V.ProjectThesisSlides
Daniil DorinSpatial-temporal characteristics in the time series decodingGrabovoy A.V.ProjectThesisSlides
Andrey VeprikovMathematical model of the hidden feedback loop effect in machine learning systemsKhritankov A.S.ProjectThesisSlides
Maria NikitinaAnalysis of distribution bias in contrastive learningIsachenko R.V.ProjectThesisSlides
Anastasia VoznyukDetection of machine-generated fragments based on text style change analysisGrabovoy A. V.ProjectThesisSlides
Anna RemizovaReducing the dimension of the space of the trainable parameters in the domain adaptation problemGrabovoy A. V.ProjectThesisSlides
Okhotnikov NikitaInterconnected latent representations for outfit generation taskIsachenko R.V.ProjectThesisSlides
Terentyev AlexanderClassification of trajectories of dynamic systems using physically-informed neural networksIsachenko R.V.ProjectThesisSlides
Ignashin IgorBayesian distillation of transformer-based modelsGrabovoy A. V.ProjectThesisSlides
Ilgam LatypovAn effective method of scalarization and search for a competitive solution without iterative calculations for Lipschitz functionsDorn Y.V.ProjectThesisSlides
Kirill SemkinTensor decomposition and forecast for multidimensional time seriesIsachenko R.V.ProjectThesisSlides
Matvei KreininOn methods with preconditioning and weight decayingBeznosikov A.N.ProjectThesisSlides
Petr BabkinDifferentiable algorithm for searching ensembles of deep learning models with diversity controlBakhteev O.Y.ProjectThesisSlides
Bogdanov AlexanderGradient approximations using a zero-order oracle and memorization techniqueBeznosikov A.N.ProjectThesisSlides
Oleinik MikhailKnowledge distillation in deep neural networks using model structure alignment methodsBakhteev O.Y.ProjectThesisSlides
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2023

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PhD’s Theses

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| Student | Thesis topic | Scientific adviser | Link to Project | Link to Paper | Link to Slides | +|:—:|:—:|:—:|:—:|:—:|:—:|

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Master’s Theses

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StudentThesis topicScientific adviserLink to ProjectLink to PaperLink to Slides
Rustem IslamovDistributed Newton-Type Methods with Communication Compression and Bernoulli AggregationStrijov V.V., Richtarik P.ProjectPaperSlides
Olga GrebenkovaAutomatic detection of focal cortical dysplasia for sparse data representationBurnaev E.V.ProjectThesisSlides
Anton BishukControlled Graph GenerationZukhba A.V.ProjectThesisSlides
Nadezhda AlsahanovaSelection of tensor representations for multiview forecastingStrijov V.V.ProjectThesisSlides
Robert SafiullinMultimodel representation of dynamic systemsStrijov V.V.ProjectThesisSlides
Shokorov ViacheslavDeep ensemble boostingVetrov D.P.ProjectThesisSlides
Filatov AndreiText Interfaces for Event SequencesStrijov V.V.ProjectThesisSlides
Viktor PankratovProbabilistic Topic Modeling for Unbalanced Text CollectionsVorontsov K.V.ProjectThesisSlides
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Bachelor’s Theses

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StudentThesis topicScientific adviserLink to ProjectLink to PaperLink to Slides
Eduard VladimirovState space models in ECoG signal classification problemStrijov V.V.ProjectPaperSlides
Georgiy ZharovSearching for links between fragments of manipulations with named entities in textsVorontsov K.V.ProjectPaperSlides
Alexander MolozhavenkoRiemannian optimization on the manifold of fixed rank tensor trains with the orthogonality conditionGasnikov A.V.ProjectPaperSlides
Ivan LukyanenkoManipulation detection in newsVorontsov. K.V.ProjectPaperSlides
Antyshev TikhonGradient Sliding for Composite Saddle Point ProblemsGasnikov A.V.ProjectPaperSlides
Kornilov NikitaGradient Free Methods for Non-Smooth Convex Stochastic Optimization with Heavy Tails on Convex CompactGasnikov A.V.ProjectPaperSlides
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2022

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PhD’s Theses

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StudentThesis topicScientific adviserLink to ProjectLink to PaperLink to Slides
Andrey GrabovoyBayesian DistilationStrijov V.V.ProjectThesisSlides
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Master’s Theses

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentThesis topicScientific adviserLink to ProjectLink to PaperLink to Slides
Alexey GrigorevRegularization of neural layer via construction of frame in parameter spaceGneushev A.N.ProjectThesisSlides
Natalia VarenikBuilding a connectivity map of functional groups in the problem of decoding brain signalsStrijov V.V.ProjectThesisSlides
Pavel SeverilovChoosing the optimal model in the problem of modeling dynamics of a physical system by neural networksStrijov V.V.ProjectThesisSlides
Panchenko SviatoslavBilinearity of geometric product for the task of signal decodingStrijov V.V.ProjectThesisSlides
Alexey GrishanovApplication of Reinforcement Learning for recommendation system personalizationVorontsov K.V.ProjectThesisSlides
Petr MokrovWasserstein gradient flows: modeling and applicationsBurnaev E.V.ProjectThesisSlides
Tikhonov DenisForecasting models selection for quasi-periodic time seriesStrijov V.V.ProjectThesisSlides
Kolesov AlexanderAdversarial training approach for a neural network in Transfer Learning problemBahteev O.Y.ProjectThesisSlides
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Bachelor’s Theses

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
StudentThesis topicScientific adviserLink to ProjectLink to PaperLink to Slides
Kurdyukova AntoninaDimensionality reduction in the phase space in canonical correlation analysisStrijov V.V.ProjectThesisSlides
Gorpinich MariyaMetaparameter optimization in knowledge distillationBakhteev O.Yu.ProjectThesisSlides
Gorсhakov VyacheslavImportance Sampling Approach to Chance-Constrained DC Optimal Power FlowMaximov Y.V.ProjectThesisSlides
Pilkevich AntonOptimization of the criterion given by the neural network model in the text detoxification taskStrijov V.V.ProjectThesisSlides
Khristolybov MaximModel parameter space for phase trajectory approximationStrijov V.V.ProjectThesisSlides
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+ + diff --git a/ru/people/aduenko_aa/index.html b/ru/people/aduenko_aa/index.html new file mode 100644 index 00000000..8963767a --- /dev/null +++ b/ru/people/aduenko_aa/index.html @@ -0,0 +1,405 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Адуенко Александр Александрович + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Интеллектуальные системы +
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+ + Machine Learning
+ + Data Analysis
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Адуенко Александр Александрович

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+ + + + + + + + + + + + + Scopus
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+  + + + + +

Окончил с отличием ФУПМ МФТИ в 2015г., в 2017г. защитил диссертацию по выбору мультимоделей в задачах классификации, кандидат физико-математических наук. Автор более 15 научных работ по байесовскому выводу и анализу данных.

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Преподает:

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+ + diff --git a/ru/people/apishev_ma/index.html b/ru/people/apishev_ma/index.html new file mode 100644 index 00000000..2d0cbe89 --- /dev/null +++ b/ru/people/apishev_ma/index.html @@ -0,0 +1,273 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Апишев Мурат Азаматович + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Интеллектуальные системы +
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+ + Machine Learning
+ + Data Analysis
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Апишев Мурат Азаматович

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+ + + + + + + Персональная страница
+ + + + + + + + Scopus
+ + + +  +
+  + + + + +

Окончил с отличием ВМК МГУ в 2017г., в 2020г. защитил диссертацию по теме “Эффективная реализация алгоритмов тематического моделирования с аддитивной регуляризацией”, кандидат технических наук.

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Автор более 8 научных работ по методам тематического моделирования. Один из создателей open-source библиотеки для тематического моделирования bigartm.

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Профессональные интересы: тематическое моделирование, параллельные алгоритмы тематического моделирования, семантические векторные представления текстовых сущностей.

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+ + diff --git a/ru/people/bakhteev_oy/index.html b/ru/people/bakhteev_oy/index.html new file mode 100644 index 00000000..f780267b --- /dev/null +++ b/ru/people/bakhteev_oy/index.html @@ -0,0 +1,438 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Бахтеев Олег Юрьевич + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Интеллектуальные системы +
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+ + Machine Learning
+ + Data Analysis
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Бахтеев Олег Юрьевич

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+ + + + + + + Персональная страница
+ + + + bakhteev(at)phystech.edu
+ + + + google scholar
+ + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

Окончил с отличием ФУПМ МФТИ в 2016, в 2020г. защитил диссертацию по методам выбора моделей глубокого обучения, кандидат физико-математических наук. Автор более 29 научных работ по методам выбора моделей и обработке естественного языка.

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Профессональные интересы: выбор моделей, глубокое обучение, нейронные сети, байесовский вывод, обработка естественного языка.

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Основные публикации

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  1. Yakovel K., Grebenkova O., Bakhteev O., Strijov V. Neural architecture search with structure complexity control // Proceedings of the 10th International Conference on Analysis of Images, Social Networks and Texts. - 2021.
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  2. Bakhteev O., Strijov V. Comprehensive analysis of gradient-based hyperparameter optimization algorithms //Annals of Operations Research. – 2020. – Т. 289. – №. 1. – С. 51-65.
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  3. Bakhteev O., Strijov V. Deep learning model selection of suboptimal complexity //Automation and remote control. – 2018. – Т. 79. – №. 8. – С. 1474-1488.
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Полный список публикаций

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Конференции и воркшопы

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  1. Bakhteev O., Ogaltsov A., Khazov A., Safin K., Kuznetsova R. CrossLang: The System of Cross-lingual Plagiarism Detection // NeurIPS, Workshop on Systems for ML. 2019.
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  2. Kuznetosva R., Bakhteev O. Variational Bi-domain Triplet Autoencoder // NeurIPS, Visually Grounded Interaction and Language workshop. 2018.
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  3. Bakhteev O., Khazov A. Author Masking using Sequence-to-Sequence Models // CLEF. 2017.
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Полный список докладов и выступлений на воркшопах

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Преподает:

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+ + diff --git a/ru/people/beznosikov_an/index.html b/ru/people/beznosikov_an/index.html new file mode 100644 index 00000000..4f54266d --- /dev/null +++ b/ru/people/beznosikov_an/index.html @@ -0,0 +1,412 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Безносиков Александр Николаевич + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Интеллектуальные системы +
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+ + Machine Learning
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Безносиков Александр Николаевич

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Окончил TODO в TODO, в TODO защитил диссертацию по TODO, кандидат физико-математических наук. Автор более TODO научных работ по TODO.

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Профессональные интересы: TODO.

+ +

Основные публикации

+
    +
  1. TODO
    2. +
  2. TODO
    3. +
+ + + + + + + + +   +
+

Преподает:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/ru/people/bishuk_ay/index.html b/ru/people/bishuk_ay/index.html new file mode 100644 index 00000000..fc69755c --- /dev/null +++ b/ru/people/bishuk_ay/index.html @@ -0,0 +1,407 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Бишук Антон Юрьевич + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Бишук Антон Юрьевич

+
+ + + + + + + + + anton.bishuk@mail.ru
+ + + + + + + +  +
+  + + + + +

В 2021 году закончил бакалавриат МФТИ. Является магистром кафедры интеллектуальных систем.

+ +

Профессиональные интересы: Активное обучение, графовые модели машинного обучения, генеративные модели.

+ + + + + + + + +   +
+

Преподает:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/ru/people/chekhovich_yv/index.html b/ru/people/chekhovich_yv/index.html new file mode 100644 index 00000000..26385973 --- /dev/null +++ b/ru/people/chekhovich_yv/index.html @@ -0,0 +1,275 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Чехович Юрий Викторович + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+
    +
+
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Чехович Юрий Викторович

+
+ + + + + + + Персональная страница
+ + + + + + google scholar
+ + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

Окончил с ФУПМ МФТИ в 1999г., в 2004г. защитил диссертацию “Элементы алгебраической теории задач синтеза обучаемых алгоритмов выделения трендов”, кандидат физико-математических наук. Автор более 93 научных работ по методам анализа данных. Под руководством Ю. В. Чеховича были защищены 3 кандидатские диссертации.

+ +

Профессональные интересы: классификационный подход к синтезу и идентификации имитационных моделей сложных социально-технических систем, моделирование транспортных систем, алгоритмы и системы обнаружения заимствований в текстовых документах.

+ + + + + + + + + + +
+ + +
+ + diff --git a/ru/people/dulin_sk/index.html b/ru/people/dulin_sk/index.html new file mode 100644 index 00000000..63db65d1 --- /dev/null +++ b/ru/people/dulin_sk/index.html @@ -0,0 +1,275 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Дулин Сергей Константинович + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+
    +
+
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Дулин Сергей Константинович

+
+ + + + + + + Персональная страница
+ + + + + + + + Scopus
+ + + eLibrary
+ + + Math-Net
+ +  +
+  + + + + +

Доктор технических наук, профессор, академик РАЕН. Автор более 95 научных работ.

+ +

Профессональные интересы: представление знаний в системах искусственного интеллекта.

+ + + + + + + + + + +
+ + +
+ + diff --git a/ru/people/filatov_av/index.html b/ru/people/filatov_av/index.html new file mode 100644 index 00000000..28426c5c --- /dev/null +++ b/ru/people/filatov_av/index.html @@ -0,0 +1,409 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Филатов Андрей Викторович + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Филатов Андрей Викторович

+
+ + + + + + + + + filatovandreiv@gmail.com
+ + + + google scholar
+ + + + + +  +
+  + + + + +

В 2021 году закончил бакалавриаит МФТИ с красным дипломом. С 2019г. является студентом кафедры интеллектуальных систем. С марта 2021 года проходит стажировку в EPFL VILAB под руководством Amir Zamir

+ +

Профессиональные интересы: Computer vision, Multi-task learning, Multi-modal learning

+ + + + + + + + +   +
+

Преподает:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/ru/people/gneushev_an/index.html b/ru/people/gneushev_an/index.html new file mode 100644 index 00000000..975c1bb4 --- /dev/null +++ b/ru/people/gneushev_an/index.html @@ -0,0 +1,275 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Гнеушев Александр Николаевич + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+
    +
+
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Гнеушев Александр Николаевич

+
+ + + + + + + Персональная страница
+ + + + + + google scholar
+ + + + + eLibrary
+ + + Math-Net
+ +  +
+  + + + + +

Кандидат физико-математических наук. Автор более 25 научных работ по метода анализа данных.

+ +

Профессональные интересы: обработка и анализ изображений, распознавание образов, биометрическая идентификация, нейросетевые модели анализа изображений, разработка моделей и методов выделения признаков для задач обнаружения и классификации объектов на изображениях, идентификация личности по лицу на изображении, обнаружение пешехода на изображении, сверхразрешение и реставрация изображений, методы моделирования и регуляризации при обучении сверточных нейронных сетей для анализа изображений, биометрическая идентификация по радужной оболочке глаза, выделение элементов лица на изображении и слежения за ними, анализ дорожной сцены, оценка скорости транспортных средств, классификация типов транспортных средств

+ + + + + + + + + + +
+ + +
+ + diff --git a/ru/people/grabovoy_av/index.html b/ru/people/grabovoy_av/index.html new file mode 100644 index 00000000..a580b976 --- /dev/null +++ b/ru/people/grabovoy_av/index.html @@ -0,0 +1,439 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Грабовой Андрей Валериевич + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Грабовой Андрей Валериевич

+
+ + + + + + + Персональная страница
+ + + + grabovoy.av@phystech.edu
+ + + + google scholar
+ + + OrcID
+ + + Scopus
+ + + + Math-Net
+ +  +
+  + + + + +

Окончил с отличием ФУПМ МФТИ в 2021., с 2021г. Является кандидатом физико-математических наук с 2022 года. Автор более 30 научных работ по выбору моделей, дистилляции знаний и обработке текста на естественном языке.

+ +

Ключевые публикации

+
    +
  1. Грабовой А.В., Стрижов В.В. Байесовская дистилляция моделей глубокого обучения // Автоматика и телемеханика, 2021.
    2. +
  2. Грабовой А.В., Стрижов В.В. Анализ выбора априорного распределениядля смеси экспертов // Журнал вычислительной математики и матема-тической физики, 2021.
    3. +
  3. A. Grabovoy, V. Strijov. Quasi-periodic time series clustering for human //Lobachevskii Journal of Mathematics, 2020.
    4. +
  4. Грабовой А.В., Бахтеев О. Ю., Стрижов В.В. Введение отношения порядка на множестве параметров аппроксимирующих моделей // Инфор-матика и ее применения, 2020.
    5. +
  5. Грабовой А.В., Бахтеев О.Ю., Стрижов В.В. Определение релевантности параметров нейросети // Информатика и ее применения, 2019.
    6. +
  6. Грабовой А.В., Стрижов В.В. Вероятностная интерпретация задачи дистилляции // Автоматика и телемеханика, 2022.
    7. +
  7. A. Grabovoy, T. Gadaev, A. Motrenko, V. Strijov Numerical methods ofminimum sufficient sample size estimation for linear models // LobachevskiiJournal of Mathematics, 2023.
    8. +
  8. A. Bazarova, A. Grabovoy , V. Strijov Analysis of the properties ofprobabilistic models in learning problems with an expert // Journal ofComputational Mathematics, 2023.
    9. +
+ +

Конференции

+
    +
  1. Задача обучения с экспертом для построения интерпретируемых моделей машинного обучения, Международная конференция «Интеллектуализация обработки информации», 2020.
    2. +
  2. Привилегированная информация и дистилляция моделей, Всероссийская конференция «63-я научная конференция МФТИ», 2020.
    3. +
  3. Введение отношения порядка на множестве параметров нейронной сети, Всероссийская конференция «Математические методы распознавания об-разов ММРО», 2019.
    4. +
  4. Анализ априорных распределений в задаче смеси экспертов, Всероссийская конференция «62-я научная конференция МФТИ», 2019.
    5. +
  5. Поиск оптимальной модели при помощи алгоритмов прореживания, Всероссийская конференция «61-я научная конференция МФТИ», 2018.
    6. +
  6. Автоматическое определение релевантности параметров нейросети, Международная конференция «Интеллектуализация обработки информации», 2018
    7. +
+ + + + + + + + +   +
+

Преподает:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/ru/people/grebenkova_os/index.html b/ru/people/grebenkova_os/index.html new file mode 100644 index 00000000..b6703a20 --- /dev/null +++ b/ru/people/grebenkova_os/index.html @@ -0,0 +1,413 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Гребенькова Ольга Сергеевна + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Гребенькова Ольга Сергеевна

+
+ + + + + + + + + grebenkova.os@phystech.edu
+ + + + + + + +  +
+  + + + + +

В 2021 году закончила бакалавриаит МФТИ с отличием. Является магистром кафедры интеллектуальных систем. Автор нескольких научных работ по машинному обучению и анализу данных.

+ +

Профессиональные интересы: генеративные модели, автоматический поиск архитектуры

+ +

Основные публикации

+ + + + + + + + + +   +
+

Преподает:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/ru/people/grishanov_av/index.html b/ru/people/grishanov_av/index.html new file mode 100644 index 00000000..9cd1f025 --- /dev/null +++ b/ru/people/grishanov_av/index.html @@ -0,0 +1,427 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Гришанов Алексей Владимирович + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Гришанов Алексей Владимирович

+
+ + + + + + + + + grishanov.av@phystech.edu
+ + + + google scholar
+ + + OrcID
+ + + + +  +
+  + + + + +

Окончил бакалавриат и магистратуру МФТИ. С 2022г. являюсь аспирантом кафедры интеллектуальных систем.

+ +

Ведущий исследователь данных Sber AI Lab

+ +

 

+ +

Профессиональные интересы: рекомендательные системы, обучение с подкреплением.

+ +

Публикации

+ +
    +
  1. +

    Grishanov A., Ianina A., Vorontsov K. Multiobjective Evaluation of Reinforcement Learning Based Recommender Systems // Proceedings of the 16th ACM Conference on Recommender Systems (RecSys ’22). Pp. 622–627.

    +
    2. +
  2. +

    Artemiev A.*, Parinov D.*, Grishanov A.*, Borisov I., Vasilev A., Muravetskii D., Rezvykh A., Goncharov A., and Savchenko A. Leveraging Summarization for Unsupervised Dialogue Topic Segmentation // Findings of the NAACL 2024.

    +
    3. +
+ + + + + + + + +   +
+

Преподает:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/ru/people/index.html b/ru/people/index.html new file mode 100644 index 00000000..b2cbbc28 --- /dev/null +++ b/ru/people/index.html @@ -0,0 +1,877 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Преподаватели + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + + + + +
+

Основатели кафедры

+
+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Рудаков Константин Владимирович +

+
+ + + + + + + + + + + + + + + + + +
+

+ + + + Воронцов Константин Вячеславович +

+
+ + + + + +
+

+ + + + Журавлев Юрий Иванович +

+
+ + +
+ +
+

Доктора наук

+
+
+ +
+ + + + + + + + + + + + + + +
+

+ + + + Дулин Сергей Константинович +

+
+ + + + + + + + + + + + + + + +
+

+ + + + Хорошевский Владимир Федорович +

+
+ + + + + + + + + +
+

+ + + + Матвеев Иван Алексеевич +

+
+ + + +
+

+ + + + Местецкий Леонид Моисеевич +

+
+ + + + + +
+

+ + + + Мохонько Елена Захаровна +

+
+ + + + + + + + + + + + + + + +
+

+ + + + Стрижов Вадим Викторович +

+
+ + + + + + + +
+

+ + + + Цурков Владимир Иванович +

+
+ + + + + +
+

+ + + + Воронцов Константин Вячеславович +

+
+ + + + + + +
+ +
+

Кандидаты наук

+
+
+ +
+ + +
+

+ + + + Адуенко Александр Александрович +

+
+ + + +
+

+ + + + Апишев Мурат Азаматович +

+
+ + + +
+

+ + + + Бахтеев Олег Юрьевич +

+
+ + + +
+

+ + + + Безносиков Александр Николаевич +

+
+ + + + + +
+

+ + + + Чехович Юрий Викторович +

+
+ + + + + + + +
+

+ + + + Гнеушев Александр Николаевич +

+
+ + + +
+

+ + + + Грабовой Андрей Валериевич +

+
+ + + + + + + +
+

+ + + + Исаченко Роман Владимирович +

+
+ + + + + + + +
+

+ + + + Хританков Антон Сергеевич +

+
+ + + +
+

+ + + + Кропотов Дмитрий Александрович +

+
+ + + + + + + +
+

+ + + + Майсурадзе Арчил Ивериевич +

+
+ + + + + + + + + + + + + + + + + + + + + +
+

+ + + + Торшин Иван Юрьевич +

+
+ + + + + + + + + + + + +
+ +
+

Аспиранты

+
+
+ +
+ + + + + + + + + + +
+

+ + + + Бишук Антон Юрьевич +

+
+ + + + + + + +
+

+ + + + Филатов Андрей Викторович +

+
+ + + + + + + +
+

+ + + + Гребенькова Ольга Сергеевна +

+
+ + + +
+

+ + + + Гришанов Алексей Владимирович +

+
+ + + + + + + +
+

+ + + + Хрыльченко Кирилл Ярославович +

+
+ + + + + + + + + + + + + + + +
+

+ + + + Мокров Петр Владимирович +

+
+ + + +
+

+ + + + Попов Артем Сергеевич +

+
+ + + +
+

+ + + + Потанин Марк Станиславович +

+
+ + + + + +
+

+ + + + Самохина Алина Максимовна +

+
+ + + +
+

+ + + + Северилов Павел Андреевич +

+
+ + + + + +
+

+ + + + Тихонов Денис Максимович +

+
+ + + + + + + +
+

+ + + + Володкевич Анна Алексеевна +

+
+ + + + + +
+

+ + + + Яковлев Константин Дмитриевич +

+
+ + + + +
+ + + + +
+ + +
+ + diff --git a/ru/people/isachenko_rv/index.html b/ru/people/isachenko_rv/index.html new file mode 100644 index 00000000..bb00539b --- /dev/null +++ b/ru/people/isachenko_rv/index.html @@ -0,0 +1,419 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Исаченко Роман Владимирович + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Исаченко Роман Владимирович

+
+ + + + + + + + + roman.isachenko(at)phystech.edu
+ + + + google scholar
+ + + + Scopus
+ + + +  +
+  + + + + +

Окончил с ФУПМ МФТИ в 2018, в 2021г. защитил диссертацию по методам снижения размерности пространства в задачах декодирования сигналов, кандидат физико-математических наук. Автор более 6 научных работ по методам интеллектуального анализа данных и обработки сигналов.

+ +

Профессиональные интересы: порождающие модели, глубокое обучение, обработка сигналов.

+ +

Основные публикации

+
    +
  1. Isachenko R., Yaushev F., Strijov V. (2021). Concordant models for latent space projections in forecasting. Systems and Means of Informatics, 31(1), 4–16.
    2. +
  2. Isachenko R., Strijov V. (2018). Quadratic Programming Optimization with Feature Selection for Nonlinear Models. Lobachevskii Journal of Mathematics, 39(9), 1179–1187.
    3. +
  3. Isachenko R., Zharikov I., Bochkarev A., Strijov V. (2018). Feature Generation for Physical Activity Classification. Artificial Intelligence and Decision Making, 3: 20–27, 2018.
    4. +
+ + + + + + + + +   +
+

Преподает:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/ru/people/khoroshevsky_vf/index.html b/ru/people/khoroshevsky_vf/index.html new file mode 100644 index 00000000..3950acc8 --- /dev/null +++ b/ru/people/khoroshevsky_vf/index.html @@ -0,0 +1,269 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Хорошевский Владимир Федорович + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+
    +
+
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Хорошевский Владимир Федорович

+
+ + + + + + + + + + + google scholar
+ + + + + eLibrary
+ + +  +
+  + + + + +

Доцент, доктор технических наук. Автор более 60 научных работ.

+ + + + + + + + + + +
+ + +
+ + diff --git a/ru/people/khrilchenko_ky/index.html b/ru/people/khrilchenko_ky/index.html new file mode 100644 index 00000000..a5a23767 --- /dev/null +++ b/ru/people/khrilchenko_ky/index.html @@ -0,0 +1,267 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Хрыльченко Кирилл Ярославович + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+
    +
+
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Хрыльченко Кирилл Ярославович

+
+ + + + + + + + + + + + + + +  +
+  + + + + +

Окончил с отличием ВМК МГУ в 2020г.

+ +

Профессональные интересы: обработка текста на естественных языках, тематическое моделирование, глубокое обучение, прикладные задачи анализа данных.

+ + + + + + + + + + +
+ + +
+ + diff --git a/ru/people/khritankov_as/index.html b/ru/people/khritankov_as/index.html new file mode 100644 index 00000000..aae96751 --- /dev/null +++ b/ru/people/khritankov_as/index.html @@ -0,0 +1,411 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Хританков Антон Сергеевич + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Хританков Антон Сергеевич

+
+ + + + + + + + + + + google scholar
+ + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

Окончил с отличием ФУПМ МФТИ в 2007г., в 2010г. защитил диссертацию по методам оценки производительности распределенных систем, кандидат физико-математических наук. Автор более 24 научных работ по оценке производительности, методам программной инженерии и системному анализу.

+ +

Профессональные интересы: Архитектура и проектирование программных систем, методологии и процессы разработки ПО, распределенные вычисления и оценка производительности.

+ + + + + + + + +   +
+

Преподает:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/ru/people/kropotov_da/index.html b/ru/people/kropotov_da/index.html new file mode 100644 index 00000000..59792fee --- /dev/null +++ b/ru/people/kropotov_da/index.html @@ -0,0 +1,409 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Кропотов Дмитрий Александрович + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Кропотов Дмитрий Александрович

+
+ + + + + + + + + + + google scholar
+ + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

Окончил с отличием ВМК МГУ в 2003г. Автор более 90 научных работ по математическим методам прогннозирования и анализу данных.

+ + + + + + + + +   +
+

Преподает:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/ru/people/matveev_ia/index.html b/ru/people/matveev_ia/index.html new file mode 100644 index 00000000..ad44d670 --- /dev/null +++ b/ru/people/matveev_ia/index.html @@ -0,0 +1,273 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Матвеев Иван Алексеевич + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+
    +
+
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Матвеев Иван Алексеевич

+
+ + + + + + + + + + + google scholar
+ + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

Окончил ФУПМ МФТИ в 1997. В 1999г. защитил диссертацию “Модели распознаваемых объектов в системе компьютерного стереозрения реального времени” на соисканиен степени кандидата физико-математических наук. В 2014г. защитил диссертацию “Методы и алгоритмы автоматической обработки изображений радужной оболочки глаза”, доктор технических наук. Автор более 95 научных работ по методам распознавания образов и анализу изображений.

+ +

Профессональные интересы: обработка изображений, распознавание образов, биометрическая идентификация.

+ + + + + + + + + + +
+ + +
+ + diff --git a/ru/people/mestetskiy_lm/index.html b/ru/people/mestetskiy_lm/index.html new file mode 100644 index 00000000..e38b647c --- /dev/null +++ b/ru/people/mestetskiy_lm/index.html @@ -0,0 +1,414 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Местецкий Леонид Моисеевич + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Местецкий Леонид Моисеевич

+
+ + + + + + + Персональная страница
+ + + + + + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

Окончил МехМат МГУ в 1971г. Доктор технических наук (1992), профессор (1998), действительный член Российской Академии естественных наук (2004). Опубликовал более 150 работ по прикладной математике, моделированию, компьютерной графике, обработке и распознаванию изображений. +Под руководством Л. М. Местецкого защитились 14 кандидатов наук.

+ + + + + + + + +   +
+

Преподает:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/ru/people/meysuradze_ai/index.html b/ru/people/meysuradze_ai/index.html new file mode 100644 index 00000000..27913465 --- /dev/null +++ b/ru/people/meysuradze_ai/index.html @@ -0,0 +1,407 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Майсурадзе Арчил Ивериевич + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Майсурадзе Арчил Ивериевич

+
+ + + + + + + + + + + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

Окончил ФУПМ МФТИ в 1999., в 2006. защитил диссертацию, кандидат физико-математических наук. Автор более 51 научных работ.

+ + + + + + + + +   +
+

Преподает:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/ru/people/mohonko_ez/index.html b/ru/people/mohonko_ez/index.html new file mode 100644 index 00000000..b34276be --- /dev/null +++ b/ru/people/mohonko_ez/index.html @@ -0,0 +1,267 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Мохонько Елена Захаровна + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+
    +
+
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Мохонько Елена Захаровна

+
+ + + + + + + + + + + + + + eLibrary
+ + +  +
+  + + + + +

Доктор физико-математических наук. Автор более 34 научных работ.

+ + + + + + + + + + +
+ + +
+ + diff --git a/ru/people/mokrov_pv/index.html b/ru/people/mokrov_pv/index.html new file mode 100644 index 00000000..cf0b7345 --- /dev/null +++ b/ru/people/mokrov_pv/index.html @@ -0,0 +1,420 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Мокров Петр Владимирович + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Мокров Петр Владимирович

+
+ + + + + + + Персональная страница
+ + + + mokrov.pv@phystech.edu
+ + + + google scholar
+ + + + + +  +
+  + + + + +

В 2022 году окончил совместную магистратуру ФПМИ МФТИ (кафеда ИАД) и Сколтеха (Data Science). Являюсь аспирантом Сколтеха, научный руководитель - Бурнаев Евгений Владимирович. Автор нескольких научных работ по машинному обучению.

+ +

Профессональные интересы: генеративные модели, оптимальный транспорт

+ +

Основные публикации

+
    +
  1. Large-scale Wasserstein Gradient Flows, NeurIPS’2021
    2. +
  2. Building the Bridge of Schrödinger: A Continuous Entropic Optimal Transport Benchmark, NeurIPS’2023
    3. +
  3. Energy-guided Entropic Neural Optimal Transport, ICLR’2024
    4. +
  4. Neural Optimal Transport with General Cost Functionals, ICLR’2024
    5. +
+ + + + + + + + +   +
+

Преподает:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/ru/people/popov_as/index.html b/ru/people/popov_as/index.html new file mode 100644 index 00000000..0eb3ee2e --- /dev/null +++ b/ru/people/popov_as/index.html @@ -0,0 +1,409 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Попов Артем Сергеевич + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Попов Артем Сергеевич

+
+ + + + + + + Персональная страница
+ + + + + + google scholar
+ + + + + +  +
+  + + + + +

Окончил ВМК МГУ в 2019г. Автор более 4 научных работ по метода обработки текста на ествественном языке и анализу данных.

+ +

Профессональные интересы: векторное представление слов, обработка текста на естественном языке, модели дистрибутивной семантики, тематические модели.

+ + + + + + + + +   +
+

Преподает:

+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + +
+ + diff --git a/ru/people/potanin_ms/index.html b/ru/people/potanin_ms/index.html new file mode 100644 index 00000000..814a4e4e --- /dev/null +++ b/ru/people/potanin_ms/index.html @@ -0,0 +1,405 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Потанин Марк Станиславович + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+
+ + +
+ +
+
+ +
+
+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
+ +

+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
+ +
+ +
+ + + + + + + + + + +
+ + + + + + +
+ +
+
+ + +
+

Потанин Марк Станиславович

+
+ + + + + + + + + + + google scholar
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Окончил МФТИ., с 2019г. является аспирантом кафедры интеллектуальных систем. Автор более 5 научных работ по машинному обучению.

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Преподает:

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+ + diff --git a/ru/people/rudakov_kv/index.html b/ru/people/rudakov_kv/index.html new file mode 100644 index 00000000..89395032 --- /dev/null +++ b/ru/people/rudakov_kv/index.html @@ -0,0 +1,4 @@ + + + + \ No newline at end of file diff --git a/ru/people/samokhina_am/index.html b/ru/people/samokhina_am/index.html new file mode 100644 index 00000000..cff39cb7 --- /dev/null +++ b/ru/people/samokhina_am/index.html @@ -0,0 +1,425 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Самохина Алина Максимовна + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ +
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+ Интеллектуальные системы +
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+ + Machine Learning
+ + Data Analysis
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Самохина Алина Максимовна

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+ + + + + + + Персональная страница
+ + + + alina.samokhina@phystech.edu
+ + + + google scholar
+ + + + + +  +
+  + + + + +

В 2019 году закончила магистратуру МФТИ. С 2021 г. является аспирантом кафедры интеллектуальных систем. Автор нескольких научных работ по машинному обучению и анализу данных.

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Профессиональные интересы: нейрокомпьютерные интерфейсы.

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Публикации

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  1. А. М. Самохина, Р. Г. Нейчев, В. В. Гончаренко, Р. К. Григорян, В. В. Стрижов Модели классификации выборки вызванных потенциалов P300 // Системы и средства информатики, 2022
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  2. Matvey Bulat, Alexandra Karpman, Alina Samokhina, Alexander Panov Playing a P300-based BCI VR game leads to changes in cognitive functions of healthy adults // BioRxiv, 2020
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Конференции

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  1. Подходы к мультиклассовой классификации датасета потенциалов P300, Международная конференция «Интеллектуализация обработки информации», 2020.
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  2. Датасет потенциалов P300 и подходы к его обработке, Всероссийская конференция «63-я научная конференция МФТИ», 2020.
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Преподает:

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+ + diff --git a/ru/people/severilov_pa/index.html b/ru/people/severilov_pa/index.html new file mode 100644 index 00000000..d821ad86 --- /dev/null +++ b/ru/people/severilov_pa/index.html @@ -0,0 +1,276 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Северилов Павел Андреевич + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ +
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+ Интеллектуальные системы +
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+ + Machine Learning
+ + Data Analysis
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Северилов Павел Андреевич

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+ + + + + + + + + severilov.pa@phystech.edu
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В TODO году закончил(а) бакалавриаит (магистратуру) МФТИ. С TODOг. является аспирантом кафедры интеллектуальных систем. Автор более TODO научных работ по машинному обучению и анализу данных.

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Профессиональные интересы: TODO.

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Основные публикации

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+ + diff --git a/ru/people/strijov_vv/index.html b/ru/people/strijov_vv/index.html new file mode 100644 index 00000000..f390c0a2 --- /dev/null +++ b/ru/people/strijov_vv/index.html @@ -0,0 +1,446 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Стрижов Вадим Викторович + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Интеллектуальные системы +
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+ + Machine Learning
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Стрижов Вадим Викторович

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+ + + + + + + Персональная страница
+ + + + strijov@ccas.ru
+ + + + google scholar
+ + + OrcID
+ + + Scopus
+ + + eLibrary
+ + + Math-Net
+ +  +
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Профессор Московского физико-технического института. Заведующий Кафедрой интеллектуальных систем МФТИ. Окончил Уфимский Государственный Авиационный Технический Университет в 1992 году. В 2002 году получил ученую степень кандидата физико-математических наук, работа посвящена методам согласования экспертных оценок. В 2012 году получил ученую степень доктора физико-математических наук, работа посвящена порождению и выбору вероятностных моделей. Автор более двухсот научных работ по машинному обучению и анализу данных. Лауреат премии имени Ильи Сегаловича за вклад в развитие научного сообщества. Под его руководством защищены восемь кандидатских диссертаций.

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Профессиональные интересы: машинное обучение, функциональный анализ данных, порождение и выбор вероятностных моделей, байесовское мультмиоделирование, анализ пространственно-временных рядов, анализ биомедицинских сигналов.

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Основные публикации

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Преподает:

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+ + diff --git a/ru/people/tikhonov_dm/index.html b/ru/people/tikhonov_dm/index.html new file mode 100644 index 00000000..29d4f7d7 --- /dev/null +++ b/ru/people/tikhonov_dm/index.html @@ -0,0 +1,406 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Тихонов Денис Максимович + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Интеллектуальные системы +
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+ + Machine Learning
+ + Data Analysis
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Тихонов Денис Максимович

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+ + + + + + + tihonov.dm@phystech.edu
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Окончил бакалавриат и магистратуру МФТИ в 2022 году. +С 2022 является аспирантом кафедры интеллектуальных систем.

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Профессиональные интересы: time series, dynamic, signals (EEG/MEG/fMRI)

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Преподает:

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+ + diff --git a/ru/people/torshin_iy/index.html b/ru/people/torshin_iy/index.html new file mode 100644 index 00000000..114b6a9c --- /dev/null +++ b/ru/people/torshin_iy/index.html @@ -0,0 +1,412 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Торшин Иван Юрьевич + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Интеллектуальные системы +
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+ + Machine Learning
+ + Data Analysis
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Торшин Иван Юрьевич

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+ + + + + + + Персональная страница
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+ + + eLibrary
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Кандидат химических наук, кандидат физико-математических наук. Автор более 600 научных работ по информатике, прикладной математике, биомедицине, биоинформатике, биофизике и химии.

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Профессональные интересы: “метрические” и “бинарные” подходы к постановке и решению плохо-формализованных задач, порождение проблемно-ориентированных метрик и анализ метрических конфигураций, комбинаторная теория разрешимости, теория классификации значений признаков, +теория графов и её комбинаторные приложения в хемоинформатике, интеллектуальный анализ данных биомедицинских исследований, комплекс задач из области биоинформатики

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Преподает:

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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + diff --git a/ru/people/tsurkov_vi/index.html b/ru/people/tsurkov_vi/index.html new file mode 100644 index 00000000..23c81fc6 --- /dev/null +++ b/ru/people/tsurkov_vi/index.html @@ -0,0 +1,273 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Цурков Владимир Иванович + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ +
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+ Интеллектуальные системы +
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+ + Machine Learning
+ + Data Analysis
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Цурков Владимир Иванович

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+ + + + + + + Персональная страница
+ + + + + + google scholar
+ + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

Окончил МФТИ в 1968г., в 1972г. защитил диссертацию на соискание степени кандидата физико-математических наук. в 1984. защитил диссертацию на соискание степени доктора физико-математических наук. Доктор физико-математических наук, академик РАЕН. Автор более 111 научных работ.

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+ + diff --git a/ru/people/volodkevich_aa/index.html b/ru/people/volodkevich_aa/index.html new file mode 100644 index 00000000..bd59234f --- /dev/null +++ b/ru/people/volodkevich_aa/index.html @@ -0,0 +1,407 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Володкевич Анна Алексеевна + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ Интеллектуальные системы +
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+ + Machine Learning
+ + Data Analysis
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Володкевич Анна Алексеевна

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Окончила совместную магистерскую программу ФКН ВШЭ и Школы Анализа Данных “Науки о данных (Data Science)” в 2020 году.

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Профессиональные интересы: рекомендательные системы, моделирование поведения пользователей

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Преподает:

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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + diff --git a/ru/people/vorontsov_kv/index.html b/ru/people/vorontsov_kv/index.html new file mode 100644 index 00000000..374983f4 --- /dev/null +++ b/ru/people/vorontsov_kv/index.html @@ -0,0 +1,417 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Воронцов Константин Вячеславович + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
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+ + +
+ +
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+ +
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+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Воронцов Константин Вячеславович

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+ + + + + + + Персональная страница
+ + + + + + google scholar
+ + + + Scopus
+ + + eLibrary
+ + +  +
+  + + + + +

Окончил МФТИ в 1994г., в 1999. защитил диссертацию на соискание степени кандидата физико-математических наук “Локальные базисы в алгебраическом подходе к проблеме распознавания”. в 2010. защитил диссертацию на соискание степени доктора физико-математических наук “Комбинаторная теория надёжности обучения по прецедентам”. Доктор физико-математических наук, профессор РАН. Автор более 115 научных работ по машинному обучению и анализу данных. Под руководством К. В. Воронцова были защищены 17 кандидатских диссертаций.

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Профессональные интересы: науки о данных, интеллектуальный анализ данных, машинное обучение, распознавание образов, прогнозирование, математическая статистика, дискретная математика, численные методы оптимизации, аналитика больших данных, а также практический анализ данных в разнообразных областях

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Преподает:

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+ + diff --git a/ru/people/yakovlev_kd/index.html b/ru/people/yakovlev_kd/index.html new file mode 100644 index 00000000..9657b077 --- /dev/null +++ b/ru/people/yakovlev_kd/index.html @@ -0,0 +1,406 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Яковлев Константин Дмитриевич + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + +
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+ +
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+ Интеллектуальные системы +
+ + + +

+ + Machine Learning
+ + Data Analysis
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+ + + + + + English + + + + + • + + + + Русский + + + + + + + + | + + + + + +
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Яковлев Константин Дмитриевич

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Окончил бакалавриат и магистратуру МФТИ в 2024 году. +С 2024 является аспирантом кафедр интеллектуальных систем и МОУ.

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Профессиональные интересы: TODO

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Преподает:

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