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October 6, 2026
International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod Brings Together Scientists from Russia and Serbia
The International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod’ was held at the Nizhny Novgorod House of Scientists from September 23 to 26. The event was organised by HSE University–Nizhny Novgorod and the Nizhny Novgorod House of Scientists, with the participation of Sberbank and the Institute of Physics Belgrade. The symposium was held for the second time: the first conference took place in 2025 and attracted considerable interest from the academic community.
October 5, 2026
‘The Climate Transition Is Not Necessarily a Limitation for Business
Linara Khadimullina works in the field of low-carbon development. In an interview with the Young Scientists of HSE project, she spoke about why nature is not just a beautiful backdrop, her research on the role of sustainable corporate governance in reducing greenhouse gas emissions, and growing plants as a source of inspiration.
October 5, 2026
Africa, Youth, and Civic Dialogue: Public Diplomacy Discussed at HSE University
In late September, HSE University hosted a roundtable discussion titled Civil Society in African Countries and Youth Participation in Public Diplomacy. Representatives of non-governmental organisations from Ghana, Ethiopia, and Russia, along with students from HSE University’s Bachelor’s Programme in Public Administration, discussed how young people without official diplomatic status can influence relations between countries and how the nonprofit sector can remain sustainable amid declining grant funding.

 

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Formal Concept Analysis for Evaluating Intrinsic Dimension of a Natural Language

Lecture Notes in Computer Science. 2023. P. 331–339.
Kuznetsov S., Gromov V., Borodin N., Divavin A.

Some results of a computational experiment for determining the intrinsic dimension of linguistic varieties for the Bengali and Russian languages are presented. At the same time, both sets of words and sets of bigrams in these languages were considered separately. The method used to solve this problem was based on formal concept analysis algorithms. It was found that the intrinsic dimensions of these languages are significantly less than the dimensions used in popular neural network models in natural language processing.

Research target: Computer Science
Language: English
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Keywords: Formal Concept AnalysisIntrinsic dimensionLanguage manifold
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