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  • Влияние маркетинговых практик на прибыльность компаний: исследование методом машинного обучения
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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
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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.
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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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Влияние маркетинговых практик на прибыльность компаний: исследование методом машинного обучения

Российский журнал менеджмента. 2016. Т. 14. № 4. С. 3–20.
Лагутаева Д. А., Tretyak O., Григорьев А. Ю.

This paper addresses the question of existence of relationships between usage of contemporary marketing practices and profitability for companies operating on the Russian market. To address this issue, we utilize an artificial intelligence method that so far was barely present in marketing and management science. The paper is not only promoting a novel research method, it also establishes the relationships between profitability and specific sets of marketing practices. We show that the companies having negative profitability make use of a wide spectrum of marketing practices (with an exception of interactive marketing) and they do not prioritize any specific types of practices. In contrary, profitable companies intensively use interactive marketing and also combine it with IT-marketing and network marketing. This shows that successful companies focus on relationship marketing in a variety of its forms.

Research target: Economics and Management
Priority areas: management
Language: Russian
Full text
Keywords: машинное обучениеклассификацияприбыльностьprofitabilityclusteringclassificationмаркетинговые практикиartificial intelligence marketing practicestypology of marketing practicesтипология маркетинговых практик
Publication based on the results of:
Business model: procedure of diagnostics and testing and validation of business models development for different industries  (2016)
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