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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Large-Scale and Distributed Optimization

Vol. 2227. Springer, 2018.
Giselsson P., Rantzer A.

This book presents tools and methods for large-scale and distributed optimization. Since many methods in "Big Data" fields rely on solving large-scale optimization problems, often in distributed fashion, this topic has over the last decade emerged to become very important. As well as specific coverage of this active research field, the book serves as a powerful source of information for practitioners as well as theoreticians.
Large-Scale and Distributed Optimization is a unique combination of contributions from leading experts in the field, who were speakers at the LCCC Focus Period on Large-Scale and Distributed Optimization, held in Lund, 14th–16th June 2017. A source of information and innovative ideas for current and future research, this book will appeal to researchers, academics, and students who are interested in large-scale optimization.

Chapters
Mirror Descent and Convex Optimization Problems with Non-smooth Inequality Constraints
Bayandina A., Dvurechensky P., Gasnikov A. et al., , in: Large-Scale and Distributed OptimizationVol. 2227.: Springer, 2018. P. 181–213.
We consider the problem of minimization of a convex function on a simple set with convex non-smooth inequality constraint and describe first-order methods to solve such problems in different situations: smooth or non-smooth objective function; convex or strongly convex objective and constraint; deterministic or randomized information about the objective and constraint. Described methods are based ...
Added: October 29, 2020
Research target: Mathematics
Language: English
DOI
Text on another site
Keywords: applied optimizationAlgorithms for Discrete OptimizationApplications of Optimizations
Large-Scale and Distributed Optimization
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Non-linear in-band interference cancellation on base of conjugate gradients method
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This paper investigates one possible solution to the problem of self-interference cancellation (SIC) arising in the design of in-band full-duplex (IBFD) communication systems. Self-interference cancellation is performed in the digital domain using multilayer nonlinear models adapted via gradient-based optimization. The presence of local minima and saddle points during the adaptation of multilayer models limits the ...
Added: May 26, 2026
New Numerical Invariants of an Unfolding of a Polycycle “Tears of the Heart”
Ilyashenko Y., Shilin I., Stanislav Minkov, Russian Journal of Mathematical Physics 2026 Vol. 33 No. 1 P. 89–106
In this paper, new numerical invariants of structurally unstable vector fields in the plane are found. One of the main tools is an improved asymptotics of sparkling saddle connections that occur when a separatrix loop of a hyperbolic saddle breaks. Another main tool is a new topological invariant of two arithmetic progressions, both perturbed and unperturbed, on the ...
Added: May 26, 2026
ADDITIVE AUTOMORPHISMS OF REGULAR MATRIX GRAPH
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Added: May 25, 2026
Coping with AI errors with provable guarantees
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AI errors pose a significant challenge, hindering real-world applications. This work introduces a novel approach to cope with AI errors using weakly supervised error correctors that guarantee a specific level of error reduction. Our correctors have low computational cost and can be used to decide whether to abstain from making an unsafe classification. We provide ...
Added: May 23, 2026
Overcoming the Curse of Dimensionality with Synolitic AI
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Added: May 23, 2026
Stable On-the-Fly Learning for Dynamic Neural Networks With Delayed Inputs
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This study presents on-the-fly identification and multi-step prediction of nonlinear systems with delayed inputs using a dynamic neural network combined with a smooth projection onto ellipsoids. The projection enforces parameter constraints that guarantee stability, while a Lyapunov–Krasovskii analysis yields computable ultimate error bounds. Riccati-type matrix inequalities are derived, providing an efficient vectorization–projection–devectorization implementation suitable for ...
Added: May 22, 2026
Analysis of the alternating minimization method for low-rank canonical polyadic decomposition in the Chebyshev norm
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The approximation of tensors in a low-para metric format is a crucial component in many mathematical modelling and data analysis tasks. Among the widely used low-parametric representations, the canonical polyadic (CP) decomposition is known to be very efficient. Nowadays, most algorithms for CP approximation aim to construct the approximation in the Frobenius norm; however, some ...
Added: May 22, 2026
B-facets in Dimension 4
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A B-facet is a lattice -dimensional polytope in the positive octant  with a positive normal covector, such that every -dimensional simplex with vertices in it is a B-simplex (i.e., a pyramid of height one with base on a coordinate hyperplane). B-facets were introduced in [2] in the context of the monodromy conjecture. In this paper, we complete the ...
Added: May 21, 2026
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Added: May 20, 2026
Upper bounds for Steklov eigenvalues of a hypersurface of revolution
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Added: May 19, 2026
On smooth Fano threefolds with coregularity zero
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Классификация градиентно-подобных потоков без гетероклинических пересечений на четырехмерных многообразиях
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Added: May 18, 2026
2-Elliptic Periodic Orbits near a Nonsimple Homoclinic Tangency in Four-Dimensional Symplectic Maps
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Added: May 15, 2026
Bibliometric Analysis by Network Models
Aleskerov F. T., Khutorskaya O., Stepochkina A. et al., Springer, 2026.
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Added: May 15, 2026
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We develop a machine-learning approach to reproduce the behavior of two versions of the van der Pol oscillator exhibiting a subcritical Andronov–Hopf bifurcation, with or without a codimension-2 Bautin point. We construct a neural-network model that functions as a recur rent map and train it on short segments of oscillator trajectories. The results show that, ...
Added: May 15, 2026
Bifurcations and Structural Stability of Generic PC-HC Families
Dorovskiy A., / Series arXiv "math". 2026.
In this paper the structural stability of generic families of vector fields of the PC-HC class on the two-dimensional sphere is proved. A classification of these families up to moderate equivalence in neighborhoods of their large bifurcation supports is presented, based on such invariants as the configuration and the characteristic set. The realization lemma is proved. ...
Added: May 14, 2026
The Sobolev space W_2^{1/2}: Simultaneous improvement of functions by a homeomorphism of the circle
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Added: May 14, 2026
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Added: November 10, 2020
DEStech Transactions on Computer Science and Engineering
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Added: June 5, 2019
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Added: October 18, 2017
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Kondrashova E. V., , in: 2015 Second International Conference on Mathematics and Computers in Sciences and in Industry (MCSI). Sliema, Malta, August 17-19, 2015.: Denver: IEEE Computer Society, 2015. P. 138–144.
The present paper is devoted to the research of controlled queueing model at control of Controlled Batch Semi-Markov Arrival Process (CBSMAP). Note that it is very reasonable to change the characteristics of arrival flows in various queueing models for optimization of its functioning. The control is based on the theory of controlled semi-markov processes for ...
Added: October 1, 2015
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Optimization, simulation and control are very powerful tools in engineering and mathematics, and play an increasingly important role. Because of their various real-world applications in industries such as finance, economics, and telecommunications, research in these fields is accelerating at a rapid pace, and there have been major algorithmic and theoretical developments in these fields in ...
Added: December 19, 2012
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