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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
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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.’
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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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?

Estimating the probability of forecasted events

International Journal of Accounting and Economics Studies. 2016. Vol. 4. No. 1. P. 76–80.
Madera A. G.

The article elaborates a method for estimating the probabilities of occurrence of prognosticated events in future. On the basis of the data from the previous periods about prognosticating the relevant events, as well as the data about the trends observed at present, two matrices are formed, the product of which is the matrix for the prognosis errors committed by the individual or the expert. The article shows that the vector for probabilities of the prognosticated events is the eigenvector of the prognosis error matrix, which corresponds to its single eigenvalue. Application of the elaborated method is shown on the definite example for forecasting demand of new products

Language: English
Keywords: probabilityEigenvalueeigenvectoreventsforecast
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