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September 7, 2026
Biologists Discover 'Molecular Fingerprint' of Preeclampsia
Researchers at HSE University employed a new method to model hypoxia in placental cells during pregnancies complicated by preeclampsia and identified molecular markers of tissue hypoxia. Since hypoxia is one of the key mechanisms underlying preeclampsia, these findings are important for a more accurate and timely diagnosis of the disease and for the development of effective treatment methods. The paper has been published in Placenta.
September 7, 2026
‘Speech, Facial Expressions, and Gestures Cannot Lie
Would you like to know whether a speaker’s trembling voice or an accidental gesture can give them away? At HSE University in Nizhny Novgorod, researchers are developing an algorithm that analyses speech, facial expressions, and gestures, and determines whether information is truthful with 92% accuracy. The project has applications ranging from forensic examination and bank recruitment to fundamental research. Anna Khomenko, head of the research group and Senior Research Fellow at the Centre for Language and Brain at the HSE Faculty of Humanities in Nizhny Novgorod, explains how students and researchers are working together to create a corpus of video recordings, train a classifier, and prepare to introduce computer vision technology.
September 4, 2026
Time to Showcase Your Research: Applications Are Now Open for Student Research Paper Competition 2026
Taking part in the Student Research Paper Competition (SRPC) gives you an opportunity to present your research to experts, receive an independent assessment, and determine the future direction of your work. The competition is open to students graduating in 2026 not only from HSE University but from universities in Russia and abroad. Papers may be submitted in Russian and English, and in some fields also in French, German, and Spanish.

 

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Proceedings of the 42nd Conference on Uncertainty in Artificial Intelligence (UAI), PMLR Volume 337, 17-21 August 2026, KIT, Amsterdam, the Netherlands

Vol. 337. Proceedings of Machine Learning Research , 2026.
Chapters
Gaussian Approximation and Multiplier Bootstrap for Federated Linear Stochastic Approximation
Levin I., Shuklin M., Moulines E. et al., , in: Proceedings of the 42nd Conference on Uncertainty in Artificial Intelligence (UAI), PMLR Volume 337, 17-21 August 2026, KIT, Amsterdam, the NetherlandsVol. 337.: Proceedings of Machine Learning Research , 2026. Ch. 134 P. 3487–3545.
In this paper, we establish Berry-Esseen-type bounds for federated linear stochastic approximation (LSA). Our results provide the first federated {Gaussian} approximations for LSA that explicitly capture communication-computation trade-offs and heterogeneity-aware error terms, quantifying the effects of local step size, number of local updates, and heterogeneity on convergence rates. We present results for both (i) constant ...
Added: September 4, 2026
Research target: Computer Science
Language: English
Text on another site
Keywords: machine learning techniques
Proceedings of the 42nd Conference on Uncertainty in Artificial Intelligence (UAI), PMLR Volume 337, 17-21 August 2026, KIT, Amsterdam, the Netherlands
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Oil Spill Segmentation in SAR Data Using ViT-UNet: Performance and Practical Insights
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Oil spill segmentation in Synthetic Aperture Radar (SAR) images is limited by noisy annotations in publicly available datasets and by architectural choices that interact with label quality in opposing directions. First, we introduce a manually refined version of the Deep-SAR Oil Spill (SOS) dataset, in which 36.25% of masks are corrected for false positives, missed ...
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Scalable machine learning approach to disordered s-wave superconductors
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We develop a neural network approach to solve the self-consistent Bogoliubov-de Gennes equations in strongly disordered s-wave superconductors. The method accurately reproduces inhomogeneous gap distributions and generalizes to system sizes far larger than those used in training. It reduces computational scaling from O(N6 ) to O(N2), enabling quantitative analysis of percolation phenomena and the superconductor-insulator ...
Added: September 5, 2026
On the rate of Gaussian approximation for online linear regression problems
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In this paper, we consider the problem of Gaussian approximation for the online linear regression task. We derive the corresponding rates for the setting of a constant stepsize and study the explicit dependence of the convergence rate on the problem dimension d and quantities related to the design matrix. When the number of iterations n is known in advance, ...
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A unified frequency-domain framework for tilted slice localization and ischemic stroke detection
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Acute ischemic stroke (AIS) analysis from two-dimensional (2D) clinical imaging is hindered by uncontrolled slice tilt and geometric inconsistencies that violate the assumptions of pose-agnostic deep learning (DL) models. This paper proposes a unified geometry-aware, frequency-domain framework for tilted slice localization and ischemic stroke segmentation that explicitly decouples pose estimation from lesion analysis. The method ...
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Proceedings of the 2026 Fourth International Conference on Distributed Computing and High Performance Computing (DCHPC)
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On behalf of the Organizing Committee, it is my great pleasure to extend a warm welcome to all participants of the Fourth International IEEE Conference on Distributed Computing and High-Performance Computing (DCHPC 2026), held in Tehran from May 10–11, 2026. This conference is jointly organized by the School of Computer Science at the Institute for Research in Fundamental Sciences (IPM) ...
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Discrete Markowitz Portfolio Optimization with Open-Source Classical and Quantum-Inspired Solvers: A Cross-Market Walk-Forward Study
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The cardinality-constrained Markowitz problem is NP-hard and traditionally solved with commercial MIQP solvers. Following the 2022 export restrictions that rendered both commercial MIQP software and cloud quantum platforms (IBM Quantum, D-Wave Leap) inaccessible from the Russian Federation, practitioners require open-source alternatives. This paper systematically compares three solver families for the discrete mean-variance problem: two open-source ...
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Benchmarking Synolitic Graphs for Autism Classification from Multisite Resting-State fMRI
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Background/Objectives: Synolitic graphs (SGs) were developed for task-based fMRI, where edge weights encode the discriminative power of pairwise regional features; whether similar information can be recovered from resting-state data was untested. We benchmarked SGs for autism spectrum disorder (ASD) classification using the multisite ABIDE-I dataset (871 subjects: 403 subjects with ASD, 468 typical controls; 17 sites; CC200 atlas). Methods: Using ...
Added: August 27, 2026
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Added: August 27, 2026
Characterizing the Scheduling Performance of 5G NR Base Stations Under Signaling and Data Traffic Constraints
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An adaptive image watermarking scheme using cooperation of HBA and RSA metaheuristics
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Added: August 25, 2026
Proceedings of the 2026 12th International Conference on Control, Decision and Information Technologies (CoDIT) (Italy, Bari, July 13–16, 2026)
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