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News
August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
August 21, 2026
Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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Алгоритмы расчета точных значений индексов манипулируемости для случая трех альтернатив

Журнал Новой экономической ассоциации. 2022. № 5(57). С. 14–23.
Ivanov A.

Abstract. Manipulation is a phenomenon when an agent or a group of agents misrepresent her/their preferences in the ballots in order to obtain a better outcome of the social choice. It has been proven that there is no not-dictatorial social choice rule which is nonmanipulable. There are two approaches to fi nd the least manipulable social choice rules. The fi rst one implies fi nding a theoretical formula for each rule. However, there are many known social choice rules and a list of manipulability indices which make this task very hard. The second approach is to generate a set of random profi les to obtain an approximate values of manipulability indices. We developed an algorithm which allows to get not approximate, but exact values of manipulability indices for any given social choice for the case of 3 alternatives. We provide the description of the algorithm, its optimizations, memory and time needed compared to the previously known algorithms, as well as the examples of the results.

Research target: Economics and Management Computer Science
Language: Russian
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Keywords: манипулированиеmanipulabilityvotingsocial choice rulesпроцедуры голосованияstrategic manipulationалгоритмы манипулируемостикоалиционное манипулирование
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