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News
July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.
July 20, 2026
Scientists Propose Method for More Efficient Resource Use in Machine Learning
An international group of researchers, including mathematicians from the AI and Digital Science Institute at the HSE Faculty of Computer Science, has provided a theoretical justification for a simple and computationally efficient method of estimating uncertainty in Stochastic Gradient Descent (SGD). The paper has been published on the scientific preprint server arXiv.org and presented at AISTATS 2026.

 

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Распределение времени между разными видами деятельности: обзор математических моделей

Вопросы экономики. 2024. № 11. С. 149–161.
Ter-Akopov S., Voronina N., Михайлова Н. С., Nagernyak M.

The history of time use research dates back more than 100 years. Russian scientists were among the first to conduct large-scale surveys in this field. Nowadays, this sphere has become interesting among scientists again. Rosstat has rebegun to conduct surveys on the daily time use, large-scale independent surveys have appeared, and media have increased their interest. The amount of empirical microdata that has emerged has made it possible to examine a complex concept as the household time use in ever more numbers. The purpose of this methodological overview is to describe the most significant mathematical models that have been used and are being used to study the time budgets of the population. This article overviews the first models in which time was considered as one of the means of production along with other goods, and households tried to maximize the utility function solely based on financial considerations. Then, modern models, where time is no less an important factor of well-being than material status, are represented. The article demonstrates how the new model classes that have recently emerged adapt to the data that is accessible in certain circumstances, modify themselves to accomplish fresh tasks, and become less costly when looking at analytical estimations. In order to categorize the population’s time budget structure under different research activities, the paper examines and systemsatizes a number of mathematical models.

Research target: Social Sciences
Language: Russian
DOI
Text on another site
Keywords: mathematical modelsфункция полезностиutility functiondiscrete choice modelstime useбюджет временимодели дискретного выбораtime budgets time allocationTobit modelТобит модельраспределение времени
Publication based on the results of:
Life Choices: Factors and Mechanisms for Making Key Decisions at Different Life Stages (2024)
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