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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.
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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В ожидании нативных архитектур СУБД на основе энергонезависимой основной памяти

Труды Института системного программирования РАН. 2020. Т. 32. № 1. С. 153–180.
С.Д. Кузнецов

Many experts in the field of data management believe that the emergence of non-volatile byte-addressable main memory (NVM) available for practical use will lead to the development of a new type of ultra-high-speed database management systems (DBMS) with single-level data storage (native in-NVM DBMS). However, the number of researchers who are actively engaged in research of architectures of native in-NVM DBMS has not increased in recent years. The most active researchers are PhD students that are not afraid of the risks, which, of course, exist in this new area. The second section of the article discusses the state of the art in NVM hardware. The analysis shows that NVM in the DIMM form factor has already become a reality, and that in the near future we can expect the appearance on the market NVM-DIMMs with the speed of conventional DRAM and endurance close to that of hard drives. The third section is devoted to the review of related works, among which the works of young researchers are the most advanced. In the fourth section, we state and justify that the work performed so far in the field of in-NVM DBMS, did not lead to the emergence of a native architecture. This is hampered by the set of limiting factors analyzed by us. In this regard, in the fifth section, we present a sketch of the native architecture of an in-NVM DBMS, the choice of which is influenced only by the goals of simplicity and efficiency. In conclusion, we summarize the article and argues the need for additional research into many aspects of the native architecture of an in-NVM DBMS.

Priority areas: IT and mathematics
Language: Russian
DOI
Text on another site
Keywords: индексацияtransaction managementquery optimizationоптимизация запросовdatabase management systemсистема управления базами данныхnon-volatile main memoryЭнергонезависимая основная память Indexingsingle-level storageодноуровневое хранение данныхуправление транзакциями
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