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News
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.
July 16, 2026
Team Success: Aligning Means with Objectives
In corporations, sports, and academia, people often face challenges they cannot handle alone. In such cases, selecting the right team is crucial. Tatiana Mayskaya, Associate Professor at the HSE Faculty of Economic Sciences and the International College of Economics and Finance, together with colleagues from foreign universities, examined team characteristics and found that less diverse teams are better suited to objectives where a high average performance is important, whereas more diverse teams are preferable when avoiding failure is critical. The paper has been published in Economic Theory.
July 15, 2026
Economists Propose More Effective Approach to Reducing Smoking
Economists at HSE University have examined how smokers respond to changes in cigarette prices. When tobacco prices increase, cigarette consumption does not always decline. In fact, spending on tobacco may even rise: according to the researchers, a 1% decrease in cigarette affordability leads to a 0.28% increase in per capita tobacco expenditure. The findings suggest that to reduce smoking rates, tobacco prices must rise faster than household incomes. The study has been published in Voprosy Statistiki.

 

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?

Online Recommender System for Radio Station Hosting

P. 1–12.
Ignatov D. I., Konstantinov A. V., Nikolenko S. I., Poelmans J., Zaharchuk V. V.

We describe a new recommender system for the Russian interactive radio network FMhost. The underlying model combines collaborative and user-based approaches. The system extracts information from tags of listened tracks for matching user and radio station profiles and follows an adaptive online learning strategy based on user history. We also provide some basic examples and describe the quality of service evaluation methodology.

Language: English
Full text
Text on another site
Keywords: music recommender systemsinteractive radio networke-commercequality of serviceэлектронная коммерциярекомендательные системы музыкиинтерактивная радиосеть

In book

Perspectives in Business Informatics Research. 11th International Conference, BIR 2012, Nizhny Novgorod, Russia, September 2012 Proceedings
Perspectives in Business Informatics Research. 11th International Conference, BIR 2012, Nizhny Novgorod, Russia, September 2012 Proceedings
Issue 128. , Berlin, Heidelberg: Springer, 2012.
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