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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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Влияние предыдущих знаний на открытие правил категоризации и их изменение в процессе использования

Психология. Журнал Высшей школы экономики. 2014. Т. 11. № 1. С. 164–173.
Kotov A. A., Бангура М.

Our experimental study looked into the way existing knowledge influences the way subjects con- struct the rules of categorization and modify them as they are applied. We modified the experiment of E. Wisniewski and D. Medina (1994) by asking the respondents not only to create a categorization rule, but also to use it to categorize new images, and we looked at the frequency and type of subsequent rule modification. The respondents, 114 university students, were given a set of images drawn by children and asked to identify their common features under one of the four conditions: relevant prior knowledge (participants were told that the drawings had been made by children with high and low creativity), stan- dard condition (participants were told the drawings had been made by children from groups A and B), standard condition with examples (one sample of drawings from each group was shown), and irrelevant knowledge. We found that under the relevant prior knowledge condition, compared to the other three conditions, the respondents tended to construct more complex and abstract rules and to change them more frequently when they categorized new objects. We also found that rule modifications during usage led to more complex and abstract rules under all four conditions. We interpret the findings as evidence for two stages of categorization, the first stage involving search for existing generalizations in semantic memory, and the second stage involving adaptation of prior knowledge to current conditions. 

 

Research target: Psychology
Priority areas: humanitarian
Language: Russian
Full text
Keywords: категоризацияcategorizationСловесный ярлыкconcept formationlabelsemantic memoryформирование понятийсемантическая память
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