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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.
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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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Российские рабочие: финансовое поведение и установки

Мониторинг общественного мнения: Экономические и социальные перемены. 2015. № 125. С. 83–85.
Karavay A.

The article is based on the evidence obtained in the all-Russian study conducted by the Institute of Sociology in 2014 and provides an analysis of the specifics of the actual behavior of the Russian workers and their settings regarding their financial income. The results are compared with the common settings and behavior and, in particular, with the settings shared by the skilled mental workers. It is shown that the “degree of safety” among workers is very small due to their relative law income and consumer behavior setting caused by their habit of conspicuous consumption with its short-horizon period. Highly skilled workers, workers with average and low qualifications as well as ordinary workers employed in trade and service industries are similar in terms of their actual financial behavior and dominant settings. However, their behavior differs from that of the middle-class workers and non-working Russians.

Priority areas: economics sociology
Language: Russian
DOI
Text on another site
Keywords: финансовое поведениесоциальная структураconsumer behaviorworking classрабочий классsocial structureсберегательное поведениерабочиеworkersfinancial behaviorprofessional groupsпрофессиональные группыпотребительское поведениеsavings behavior
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