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News
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.
August 18, 2026
HSE Scholar Presents Research on Postcards in Brazil and South Korea
Timur Khusyainov, Deputy Dean of theFaculty of Humanities atHSE University–Nizhny Novgorod, took part in two international conferences—the XVI World Congress of Rural Sociology in Porto Alegre, Brazil, and the 36th Annual Conference of the Alliance of Digital Humanities Organisations (DH2026) in Daejeon, South Korea. On his way to the conferences, the researcher also visited several other places, where he presented the experience of the Pochtovoe educational project.
August 18, 2026
Physicists Discover What Happens Inside a Stable Vortex
Large vortices with characteristic spiral arms are often observed in the atmosphere and the ocean. Physicists from HSE University have explained how these structures form and why they retain their shape. The researchers found that velocities at points located along the same vortex arc remain correlated even over long distances. At the same time, this correlation weakens rapidly with increasing distance from the vortex centre. These differences help explain the formation of spiral arms and may improve models of atmospheric and oceanic currents. The findings have been published in Physical Review Fluids.

 

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?

Fast Nearest-Neighbor Classifier based on Sequential Analysis of Principal Components

Ch. 7. P. 73–80.
Sokolova A., Savchenko A.

In this paper we improve the speed of the nearest neighbor classifiers of a set of points based on sequential analysis of high-dimensional feature vectors. Each input object is associated with a sequence of principal component scores of aggregated features extracted by deep neural network. The number of components in each element of this sequence is dynamically chosen based on explained proportion of total variance for the training set.We propose to process the next element with higher explained variance only if the decision for the current element is unreliable. This reliability is estimated by matching of the ratio of the minimum distance and all other distances with a certain threshold. Experimental study for face recognition with the Labeled Faces in the Wild and YouTube Faces datasets demonstrates the decrease of running time up to 10 times when compared to conventional instance-based learning.
 

Language: English
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Keywords: face recognition principal component analysis Sequential analysishigh-dimensional features deep neural networknearest neighbor classifier
Publication based on the results of:
Methods and Algorithms for Networks Analysis (2019)

In book

Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected Papers
Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected Papers
Vol. 11832. , Cham: Springer, 2019.
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