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.
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.
The use of machine learning models makes it possible to achieve greater accuracy in predicting risks in the Russian stock market compared to classical econometric approaches. The predictive power of these models increases by 23%, while the average investor’s return can reach up to 13% per annum. These conclusions were drawn by Nikita Lysenok from the Department of Financial Market Infrastructure at the HSE Faculty of Economic Sciences. The paper has been published in Fundamental and Applied Mathematics.
Gazizov R., Gazizov R. R., Zabolotsky A. M., , in: 2018 19th International Conference of Young Specialists on Micro/Nanotechnologies and Electron Devices (EDM)Issue 19.: IEEE, 2018. P. 93–97.
Importance of the genetic algorithm (GA) and evolution strategy (ES) usage in the investigation of an ultrashort pulse peak voltage in a printed circuit board (PCB) bus of autonomous navigation system (ANS) is highlighted. Trapezoidal ultrashort pulse propagation along the conductors of the PCB bus was optimized. The optimization was made by maximization criteria of ...
Grinin L. E., Grinin A., Korotayev A., , in: Industry 4.0. Entrepreneurship and Structural Change in the New Digital Landscape.: Springer, 2017. Ch. 12 P. 243–261.
In this chapter, we analyze the relationship between Kondratieff waves and major technological revolutions on the basis of the theory of production principles and production revolutions, and offer some forecasts about the features of the Sixth Kondratieff Wave/the Fourth Industrial Revolution. We show that the technological breakthrough of the Sixth Kondratieff Wave may be interpreted ...
