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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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Method of Directed Enumeration of Alternatives in the Problem of Automatic Recognition of Half-Tone Images

Optoelectronics, Instrumentation and Data Processing. 2009. Vol. 45. No. 3. P. 255–261.
Savchenko A.

The article deals with a problem of halftone image signals recognition using the minimum of the informative divergent criterion. The new algorithm of direct search among set of alternatives using Kullback-Leibler information distance has been developed in opposition to exhaustive search between concurrent hypotheses. The experimental results have been produced. The proposed algorithm is characterized by increased accuracy and assurance factor in the problem of automatic image recognition.

Research target: Mathematics Computer Science
Priority areas: business informatics
Language: English
Full text
Keywords: распознавание образовкритерий минимума информационного рассогласованияавтоматическое распознавание изображенийautomatic image recognitionpattern recognitionrecognition with trainingcriterion of the minimum of information mismatchраспознавание с обучениемобработка изображенийматематические проблемы искусственного интеллекта
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