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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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Моногорода Уральского федерального округа: матрица рисков развития

Вопросы государственного и муниципального управления. 2022. № 3. С. 171–192.
Фомин М. В., Smirnov O., Мирязов Т. Р.

The study focuses on company towns of the Ural Federal District (UFD). Based on the analysis of the features of these settlements’ development, their typology was built as a tool for identifying the potential and promising models and scenarios of spatial development were suggested. The research is based on the analysis of statistical materials, regulatory and legislative acts of the Russian Federation, as well as unconnected observations and expert interviews conducted by the authors on expeditions in 2020–2022. The study showed that among the company towns of the UFD region, settlements with a difficult socio-economic situation or with risks of its deterioration prevail. In addition, company towns form single-industry districts in the Sverdlovsk and Chelyabinsk regions. Promising scenarios of  spatial development of  Ural mono-settlements are considered: «local» (the development of company towns only by  the administrations of cities and settlements), «regional» (participation in the development of company towns of  forces and means at the regional level) and «federal» (the development of company towns with the help of a purposeful, coordinated state policy at the level of the whole country). For a more visual visualization of the results, the mapping method in the original development was used. According to the results of the study, it is concluded that with synchronized federal and regional support, the classic resource specializations of company towns can develop in the branches of a new techno paradigm. In order to systematically improve the situation in the mono–settlements of the Urals and prevent crisis phenomena in them, first of all, measures are needed aimed at increasing the competitiveness of city-forming enterprises, as well as increasing the social burden of large businesses – owners of cityforming enterprises .

Research target: Social and Economic Geography (including Urban and Transportation Studies) Economics and Management
Language: Russian
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Keywords: моногородаУралпространственное развитиесистема расселенияUralcompany townsthe settlement systemградообразующие предприятияcity-forming enterprise spatial development
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