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News
November 10, 2026
Physicists Train AI to Optimise Particle Beams in Accelerators
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science and the Budker Institute of Nuclear Physics at the Siberian Branch of the Russian Academy of Sciences have developed RLABC (Reinforcement Learning for Accelerator Beamline Control), a framework that uses reinforcement learning to identify optimal settings for a particle accelerator. In a computer simulation, RLABC optimised the accelerator's parameters to achieve a particle transmission rate of 70%. The study has been published in Computer Physics Communications.
November 9, 2026
'Organ-on-a-Chip Technology Could Eliminate the Need for Animal Testing'
The Laboratory of Molecular Physiology at the HSE Faculty of Biology and Biotechnology investigates how molecular regulators known as microRNAs control gene expression and contribute to the development of diseases, including cancer, viral and inflammatory conditions, and pregnancy complications. At HSE University, researchers develop organ-on-a-chip models: miniature devices containing living cells that mimic the functions of human organs, such as the placenta and intestines. These models help researchers understand how diseases develop and how drugs affect them. HSE News Service spoke with Evgeny Knyazev, Head of the Laboratory.
November 9, 2026
Flattened Terrain Models Underestimate Vehicle-to-Vehicle Communication Outages
Researchers at HSE MIEM have shown that widely used simulators of vehicle-to-vehicle communication significantly overestimate its reliability because they assume flat terrain. When terrain features, bridges, and tunnels are taken into account, the outage rate on a mountain serpentine road rises from 21% to 30%, on an overpass from 20% to 33%, and in a tunnel from 0% to 80%. The results have been published in Future Transportation.

 

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Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems

Hershey : IGI Global, 2012.
Naidenova X., Ignatov D. I.
Chapters
Bimodal Cross-Validation Approach for Recommender Systems Diagnostics
Ignatov D. I., Poelmans J., , in: Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems.: Hershey: IGI Global, 2012. Ch. 8 P. 185–195.
Recommender systems are becoming an inseparable part of many modern Internet web sites and web shops. The quality of recommendations made may significantly influence the browsing experience of the user and revenues made by web site owners. Developers can choose between a variety of recommender algorithms; unfortunately no general scheme exists for evaluation of their ...
Added: December 3, 2012
Research target: Computer Science Mathematics Philology and Linguistics
Priority areas: mathematics engineering science
Language: English
Full text
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Keywords: машинное обучениеразработка данных (Data Mining)информатикаанализ формальных понятийонтологииdata miningинтеллектуальный анализ данныхknowledge discoveryобнаружение знанийрешетки Галуаmachine learningalgorithmsapriori-like bottom-up searchclosure operations of Galois connectionsdiagnostic test approachformal concept analysisontologiesweb miningанализ интернет-данныхподход диагностических тестовкибернетикаадаптивные и обучающие системыпроцессы информационного поискаматематические проблемы искусственного интеллектаматематическая кибернетикавычислительная математикаалгебра
Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems
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