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News
July 15, 2026
Economists Propose More Effective Approach to Reducing Smoking
Economists at HSE University have examined how smokers respond to changes in cigarette prices. When tobacco prices increase, cigarette consumption does not always decline. In fact, spending on tobacco may even rise: according to the researchers, a 1% decrease in cigarette affordability leads to a 0.28% increase in per capita tobacco expenditure. The findings suggest that to reduce smoking rates, tobacco prices must rise faster than household incomes. The study has been published in Voprosy Statistiki.
July 15, 2026
HSE MIEM Students to Develop Two Satellites from Scratch for Orbital Experiments
The devices, created by student teams, will conduct space research on the properties of promising solar cells, on-board energy storage systems, and serial electronics for student satellites.
July 13, 2026
Biologists Discover Unique Properties of MiR-93-5p MicroRNA in Prostate Cancer
Researchers at the International Laboratory of Microphysiological Systems of the HSE Faculty of Biology and Biotechnology investigated how different isoforms of the same microRNA influence gene function in prostate adenocarcinoma. The study found that in some cases, microRNAs can reinforce each other’s effects by targeting and suppressing the same genes. This finding offers a fresh perspective on the molecular mechanisms underlying tumour development and on the search for disease biomarkers. The results have been published in PeerJ.

 

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Advances in Neural Computation, Machine Learning, and Cognitive Research III

Springer, 2020.
Academic editor: B. Kryzhanovsky, W. Dunin-Barkowski, V. Redko, Y. Tiumentsev

This book describes new theories and applications of artificial neural networks, with a special focus on answering questions in neuroscience, biology and biophysics and cognitive research. It covers a wide range of methods and technologies, including deep neural networks, large scale neural models, brain computer interface, signal processing methods, as well as models of perception, studies on emotion recognition, self-organization and many more. The book includes both selected and invited papers presented at the XXI International Conference on Neuroinformatics, held on October 7-11, 2019, in Dolgoprudny, a town in Moscow region, Russia.

Chapters
Towards Automatic Manipulation of Arbitrary Structures in Connectivist Paradigm with Tensor Product Variable Binding
Demidovskij A., , in: Advances in Neural Computation, Machine Learning, and Cognitive Research III.: Springer, 2020. P. 375–383.
Building a bridge between symbolic and connectionist level of computations requires constructing a full pipeline that accepts symbolic structures as an input, translates them to distributed representation, performs manipulations with this representation equivalent to symbolic manipulations and translates it back to the symbolic structure. This work proposes neural architecture that is capable of joining two ...
Added: October 27, 2019
Priority areas: IT and mathematics
Language: English
DOI
Text on another site
Keywords: Facial Expression RecognitionFunctional Connectivity MethodsApplication of Tensor Train Neural Networks
Advances in Neural Computation, Machine Learning, and Cognitive Research III
Similar publications
Growth in noncommutative algebras and entropy in derived categories
Piontkovski D., / Series arXiv "math". 2026.
A noncommutative projective variety is defined, following Artin and Zhang, by a graded coherent algebra 𝐴. The category of coherent sheaves is then the quotient qgr(𝐴) of the category of finitely presented graded modules by the subcategory of torsion modules. We consider the categorical and polynomial entropies of the Serre twist, that is, of the ...
Added: June 23, 2026
Multilinear nilalgebras and the Jacobian theorem
Piontkovski D., / Series arXiv "math". 2025.
If a symmetric multilinear algebra is weakly nil, then it is Engel. This result may be regarded as an infinite-dimensional analogue of the well-known Jacobian theorem, which states that if a polynomial mapping has a polynomial inverse, then its Jacobian matrix is invertible. This refines a theorem of Gerstenhaber and partially answers a question posed ...
Added: June 23, 2026
ML-based Fast Simulation of FARICH Responses
Shipilov F., Barnyakov A., Ivanov A. et al., / Series Physics "arxiv.org". 2026.
A fast simulation of the detector response is a vital task in high-energy physics (HEP). Traditional Monte-Carlo methods form the backbone of modern particle physics simulation software but are computationally expensive. We present a machine-learning-based approach to fast simulation of the Focusing Aerogel Ring Imaging Cherenkov (FARICH) detector response. Given a particle track and momentum, ...
Added: May 19, 2026
Natural hazard database from Internet publications: text mining with a large language model
Derkacheva A., Sakirkina M., Kraev G. et al., /. 2026.
Comprehensive data on natural hazards and their consequences are crucial for effective for risk assessment, adaptation planning, and emergency response. However, many countries face challenges with fragmented, inconsistent, and inaccessible data, particularly regarding local-scale events. To address this data gap in Russia, we developed an end-to-end processing pipeline that scrapes news from various online sources, ...
Added: April 28, 2026
Algorithmic overlaps as thermodynamic variables: from local to cluster Monte Carlo dynamics in critical phenomena
Pilé I., Deng Y., Shchur L., / Series arXiv "math". 2026. No. 2604.10254.
We investigate the spatial overlap of successive spin configurations in Markov chain Monte Carlo simulations using the local Metropolis algorithm and the Svendsen-Wang and Wolff cluster algorithms. We examine the dynamics of these algorithms for two models in different universality classes: the Ising model and the Potts model with three components. The overlap of two ...
Added: April 20, 2026
Using predefined vector systems to speed up neural network multimillion class classification
Gabdullin N., Androsov I., / Series Computer Science "arxiv.org". 2026.
Label prediction in neural networks (NNs) has O(n) complexity proportional to the number of classes. This holds true for classification using fully connected layers and cosine similarity with some set of class prototypes. In this paper we show that if NN latent space (LS) geometry is known and possesses specific properties, label prediction complexity can ...
Added: April 2, 2026
Iterative Ricci-Foster Curvature Flow with GMM-Based Edge Pruning: A Novel Approach to Community Detection
Sorokin K., Beketov M., Онучин А. et al., / arxiv.org. Серия cs.SI "Social and Information Networks ". 2025.
Community detection in complex networks is a fundamental problem, open to new approaches in various scientific settings. We introduce a novel community detection method, based on Ricci flow on graphs. Our technique iteratively updates edge weights (their metric lengths) according to their (combinatorial) Foster version of Ricci curvature computed from effective resistance distance between the ...
Added: January 15, 2026
Implementing Transport Coding in OMNeT++ for Message Delay Reduction
Petrovanov I., Sergeev A., / Series Computer Science "arxiv.org". 2025. No. 2512.18332.
Transport coding reduces message delay in packet-switched networks by introducing controlled redundancy at the transport layer:  original packets are encoded into  coded packets, and the message is reconstructed after the first  successful deliveries, effectively shifting latency from the maximum packet delay to the -th order statistic. We present a concise, reproducible discrete-event implementation of transport coding in OMNeT++, including ...
Added: December 24, 2025
Hessian-based lightweight neural network for brain vessel segmentation on a minimal training dataset
Меньшиков И. А., Бернадотт А. К., Elvimov N. S., / Series arXie "Statistical mechanics". 2025.
Accurate segmentation of blood vessels in brain magnetic resonance angiography (MRA) is essential for successful surgical procedures, such as aneurysm repair or bypass surgery. Currently, annotation is primarily performed through manual segmentation or classical methods, such as the Frangi filter, which often lack sufficient accuracy. Neural networks have emerged as powerful tools for medical image ...
Added: December 1, 2025
Эффективный алгоритм торговли на фондовом рынке: ретроспективный анализ, основанный на данных по S&P-500.
Rubchinskiy A., Chubarova D., / Series WP7 "Математические методы анализа решений в экономике, бизнесе и политике". 2025. No. WP7/2025/01.
The article examines one of the most famous examples of socio-economic systems, characterized by significant uncertainty – the S&P-500 stock market, where shares of 500 largest US companies are traded. No assumptions are made about the probabilistic characteristics of the stock market. A flexible algorithm for daily trading has been developed, based on both known fixed data ...
Added: November 9, 2025
Three-way classification for sequences of observations
A. V. Savchenko, L. V. Savchenko, Information Sciences 2023 Vol. 648 Article 119540
This article introduces the novel technique to reduce the computation time for classifying a sequence of observations (frames), such as a video stream, where each observation is described by high-dimensional embeddings extracted by a deep neural network. By using the methodology of granular computing, an observed sequence is represented at various scales using different frame ...
Added: August 27, 2023
A standalone software for real-time facial analysis in online conferences and e-lessons
Churaev E., Savchenko A., Software Impacts 2023 Vol. 16 Article 100507
Nowadays, many meetings, lessons, conferences, and presentations are organized online, where it is complicated to communicate with an audience and control their engagement and emotions. In this article, we present a novel C++ application that is led to help estimate facial identities and expressions. It captures a screen with a window of an arbitrary online ...
Added: May 18, 2023
Group-Level Affect Recognition in Video Using Deviation of Frame Features
Andrey V. Savchenko, Lyudmila V. Savchenko, Belova N. S., , in: Analysis of Images, Social Networks and Texts. 10th International Conference, AIST 2021, Tbilisi, Georgia, December 16–18, 2021, Revised Selected Papers.: Cham: Springer, 2022. Ch. 13217 P. 199–207.
Added: November 5, 2022
HSE-NN Team at the 4th ABAW Competition: Multi-task Emotion Recognition and Learning from Synthetic Images
Savchenko A., / Series Computer Science "arxiv.org". 2022.
In this paper, we present the results of the HSE-NN team in the 4th competition on Affective Behavior Analysis in-the-wild (ABAW). The novel multi-task EfficientNet model is trained for simultaneous recognition of facial expressions and prediction of valence and arousal on static photos. The resulting MT-EmotiEffNet extracts visual features that are fed into simple feed-forward ...
Added: October 21, 2022
Video-based Frame-level Facial Analysis of Affective Behavior on Mobile Devices using EfficientNets
Savchenko A., , in: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).: IEEE, 2022. P. 2358–2365.
In this paper, we consider the problem of real-time video-based facial emotion analytics, namely, facial expression recognition, prediction of valence and arousal and detection of action unit points. We propose the novel frame-level emotion recognition algorithm by extracting facial features with the single EfficientNet model pre-trained on Affect-Net. The predictions for sequential frames are smoothed ...
Added: August 29, 2022
Classifying emotions and engagement in online learning based on a single facial expression recognition neural network
Savchenko A., Savchenko L., Makarov I., IEEE Transactions on Affective Computing 2022 Vol. 13 No. 4 P. 2132–2143
In this paper, behaviour of students in the e-learning environment is analyzed. The novel pipeline is proposed based on video facial processing. At first, face detection, tracking and clustering techniques are applied to extract the sequences of faces of each student. Next, a single efficient neural network is used to extract emotional features in each ...
Added: July 14, 2022
Functional connectivity of spoken language processing in early-stage Parkinson’s disease: an MEG study
Hyder R., Jensen M., Højlund A. et al., NeuroImage: Clinical 2021 No. 102718
Parkinson’s disease (PD) is a neurodegenerative disorder, well-known for its motor symptoms; however, it also adversely affects cognitive functions, including language, a highly important human ability. PD pathology is associated, even in the early stage of the disease, with alterations in the functional connectivity within corticosubcortical circuitry of the basal ganglia as well as within ...
Added: January 21, 2022
Spectral Tensor Train Parameterization of Deep Learning Layers
Obukhov A., Rakhuba M., Liniger A. et al., , in: International Conference on Artificial Intelligence and Statistics, 13-15 April 2021, VirtualVol. 130.: PMLR, 2021. P. 3547–3555.
Added: October 31, 2021
Eye movement strategies in facial expression recognition are not related to the strength of inversion and thatcherization effects
Лунякова Е. Г., Гани-Заде Д. С., The Russian Journal of Cognitive Science 2019 Vol. 6 No. 3 P. 6–13
The present research focuses on the mechanisms of facial expression recognition. We explored the relationship between eye movement strategies in face perception processes and the intensity of holistic perception effects — namely, the inversion effect. It was assumed that if holistic and feature-based mechanisms rely on certain specific image viewing strategies, the  intensity of the ...
Added: December 10, 2020
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