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News
June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
June 5, 2026
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
June 5, 2026
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

 

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Система поддержки принятия решений «ELECTRE»

Прикладная информатика. 2017. Т. 12. № 1 (67). С. 102–113.
Kravchenko T. K.

Problem statement: solutions analytical justification by using a decision support system (DSS) significantly increases the quality of decisions. The existing DSS generally employs methods analytic hierarchy process and analytical networks. It does not always lead to the desired results as each method is based on certain assumptions and is not universal. The creation of the DSS, including ELECTRE collection methods, will allow to obtain additional information about the relative importance of different variants of the solution for the task. Methodological basis for the creation the DSS «ELECTRE»: the family of ELECTRE methods, which include ELECTRE I, ELECTRE Iv, ELECTRE IS, ELECTRE II, ELECTRE III and others. Their key feature consists in the fact that they do not use the convolution operation of evaluation of the alternatives specified in different scales on different criteria. Results: developed software of DSS «ELECTRE», allowing to use any of the methods of this family to select the preferred alternatives based on multiple criteria and evaluations of their relative importance. Practical relevance: unlike other developments, the research results allow to analytically justify solutions using a variety of methods of collection in one software environment.

Research target: Computer Science Economics and Management
Priority areas: management business informatics
Language: Russian
Full text
Keywords: системы поддержки принятия решенийэкспертная система поддержки принятия решенийdecision support systemsExpert Decision Support System (EDSS)ELECTRE family methodsметоды семейства ELECTREdecision support system «ELECTRE»the task of choosing a platform for business intelligence for the enterpriseсистема поддержки принятия решений «ELECTRE»задача выбора платформы бизнес-интеллекта для предприятия
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