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  • Анализ механизмов распространения ПИИ в предприятия российской пищевой промышленности: региональные аспекты
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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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Анализ механизмов распространения ПИИ в предприятия российской пищевой промышленности: региональные аспекты

С. 215–218.
Gladysheva A. A., Ratnikova T. A.

In this research the two mechanisms of the FDI distribution in Russian food industry companies are discussed. We investigate regional characteristics and their spatial lags as determinants of the process. To test the influence of these determinants on the probability to have more than 10% of foreign capital in a company we estimate the hierarchical binary-choice models on a sample of Russian food industry companies (from RUSLANA database, on 2009). According to the results, the hierarchical diffusion of foreign investors is motivated by the seeking of local market and by seeking of the efficiency through lower transportation costs and better investment environment. The local resources in innovations are not significant on this level. When the investors develop new regions they take into account almost all the investigated regional characteristics.

Language: Russian
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Keywords: прямые иностранные инвестициитранспортная инфраструктураagglomeration effectsагломерационные эффектырегионы РоссииRussian regionstransport infrastructure Foreign Direct Investment (FDI)предприятия пищевой промышленностиspatial lagsпространственные лагиmarket potentialрыночный потенциал регионовfood industry companiesиерархическая модель бинарного выбораmultilevel binary model

In book

Системное моделирование социально-экономических процессов: труды 37-ой Международной научной школы-семинара, г. Сочи, 30 сентября - 5 октября 2014 г.
Воронеж: Воронежский государственный педагогический университет, 2014.
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