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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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Information Retrieval. 8th Russian Summer School, RuSSIR 2014, Nizhniy, Novgorod, Russia, August 18-22, 2014, Revised Selected Papers

Vol. 505. Switzerland : Springer, 2015.
Editor-in-chief: Karpov N., Ignatov D. I., Braslavski P.

This book constitutes the thoroughly refereed proceedings of the 8 th Russian Summer School on Information Retrieval, RuSSIR 2014, held in Nizhniy Novgorod, Russia, in August 2014.

The 14 papers presented  were selected from various submissions. The papers focus on visualization  for information retrieval along with other topics related  to information retrieval.

Chapters
Modelling movement of stock market indexes with data from emoticons of Twitter users
Porshnev A., Редькин И. Е., Karpov N., , in: Information Retrieval. 8th Russian Summer School, RuSSIR 2014, Nizhniy, Novgorod, Russia, August 18-22, 2014, Revised Selected PapersVol. 505.: Switzerland: Springer, 2015. Ch. 10 P. 297–306.
The issue of using Twitter data to increase the prediction rate of stock price movements draws attention of many researchers. In this paper we examine the possibility of analyzing Twitter users’ emoticons to improve accuracy of predictions for DJIA and S&P500 stock market indices. We analyzed 1.6 billion tweets downloaded from February 13, 2013 to ...
Added: February 18, 2016
Research target: Computer Science
Priority areas: business informatics
Language: English
DOI
Text on another site
Keywords: data miningdatabase management & information retrievalknowledge discovery information retrievalArtificial Intelligence (incl. Robotics)
Information Retrieval. 8th Russian Summer School, RuSSIR 2014, Nizhniy, Novgorod, Russia, August 18-22, 2014, Revised Selected Papers
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