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On the optimal rank-1 approximation of matrices in the Chebyshev norm
Linear Algebra and its Applications. 2023. Vol. 679. P. 4–29.
Stanislav Morozov, Smirnov M., Zamarashkin N.
The problem of low rank approximation is ubiquitous in science. Traditionally this problem is solved in unitary invariant
norms such as Frobenius or spectral norm due to existence of efficient methods for building approximations. However, recent results reveal the potential of low rank approximations in Chebyshev norm, which naturally arises in many applications. In this paper we tackle the problem of building optimal rank-1 approximations in the Chebyshev norm. We investigate the properties of alternating minimization algorithm for building the low rank approximations and demonstrate how to use it to construct optimal rank-1 approximation. As a result we propose an algorithm that is capable of building optimal rank-1 approximations in Chebyshev norm for moderate matrices.
Springer, 2026.
This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the XIV International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2025). The carefully selected papers cover ...
Added: October 13, 2026
Springer, 2026.
This book offers a comprehensive overview of the latest research, innovations, and practical applications in the field of sustainability, with a focus on construction materials and their use in building and civil engineering structures. As an outcome of the 3rd International Conference on Sustainability: Developments and Innovations (ICSDI 2026), this book presents a selection of ...
Added: October 13, 2026
Dmitriev A., Kornilov V., Batienkov R., Lecture Notes in Civil Engineering 2026 Vol. 886 P. 249–255
Numerous studies have provided compelling evidence that the probability distribution of avalanche sizes follows a power law, and that 1/f noise is present in the stochastic dynamics of landslides. We present a theoretical explanation of these phenomena within the framework of self-organized criticality theory, proposing a discrete-time model in the form of a sandpile cellular ...
Added: October 13, 2026
Dmitriev A., Shulman I., Lebedev A., Studies in Computational Intelligence 2026 Vol. 1265 P. 266–273
A discrete-time model is presented for the self-organization of the X/Twitter social network to the edge of a phase transition, characterized by avalanche-like propagation of information in the network. The model is based on the analogy between the critical dynamics of the X social network and sandpile cellular automata with Manna rule on the Chung-Lu ...
Added: October 13, 2026
Makarov D. M., Kalikin N., Fashchevsky K. A. et al., Electrochimica Acta 2026 Vol. 579 Article 150159
Machine learning (ML) has become a powerful tool for accelerating the development of carbon-based supercapacitors;
however, most published models assume that a single predictive framework can describe both conventional
porous carbons and hybrid carbon electrodes. Here, we test this assumption using a comprehensive
benchmark dataset and an extended literature-curated dataset enriched with synthesis- and electrolyte-related
descriptors. Three ML algorithms ...
Added: October 13, 2026
Zhang Z., Ilvovsky D., Information Processing and Management 2026 Vol. 63 No. 7
Transformer-based Large Language Models (LLMs) rely on Key-Value (KV) cache to accelerate autoregressive decoding, but memory and compute requirements still grow with context length, limiting deployment on resource-constrained devices. Existing training-free KV cache compression methods mainly rely on attention-driven retention heuristics, which may under preserve structurally informative tokens under tight cache budgets, especially when such ...
Added: October 13, 2026
Gusein-Zade S., Campillo A., Delgado F., Mathematische Zeitschrift 2026 Vol. 314 No. 1 P. 1–22
For a subfield $\K$ of the field $\C$ of complex numbers, we consider curve and divisorial valuations on the algebra $\K[[x,y]]$ of formal power series in two variables with the coefficients in $\K$. We compute the semigroup Poincar\'e series and the classical Poincar\'e series of a (discrete, rank one) valuation on it. ...
Added: October 13, 2026
No Species Is an Island, Entire of Itself: Genetic Speciation Algorithm with Interplay among Species
International Journal of Engineering, Transactions B: Applications 2027 Vol. 40 No. 5 P. 1437–1460
This paper, with a particular emphasis on Genetic Algorithm (GA), proposes a novel approach that integrates clustering mechanisms, predator-prey dynamics, and a distinctive selection strategy for generating subsequent populations. The proposed evolutionary algorithm, referred to as Genetic Speciation Algorithm with Interplay Among Species (GSAIS), is comprehensively evaluated against several variants of GAs as well as ...
Added: October 12, 2026
Mishuris G., Meylan M. H., Pelinovsky E., Journal of Fluid Mechanics 2026 Vol. 1045 Article A4
In this paper, we revisit the classic problem of a wave field on a sloping beach of an arbitrary angle and propose a general approach that allows the computation of regular solutions of the problem regardless of the angle. We use the Mellin-transform technique, reducing the problem to singular integral equations with fixed-point singularities of ...
Added: October 12, 2026
Alexandrov D., Vasilevsky V., Rezunik L. et al., Труды Института системного программирования РАН 2026 Т. 38 № 5 С. 73–90
Large language models demonstrate limitations in tasks that require precise information retrieval from very long input sequences. This limitation affects code generation in large object-oriented systems, where correctness depends on complex inter-class dependencies and the analysis of long execution traces that exceed standard context window sizes. This paper presents JavaCapsule, a technology for automated generation ...
Added: October 12, 2026
Singapore: Springer, 2026.
This volume presents the Proceedings of the 34th IUPAP Conference on Computational Physics (CCP2023), held in Kobe, Japan on August 4–8, 2023. It offers a collection of peer-reviewed articles that highlight recent developments in computational and simulation research across various areas of physics. Key topics include the use of data science, quantum computing, and machine ...
Added: October 12, 2026
Gusein-Zade S., М.: МЦНМО, 2026.
Книга содержит курс лекций по дифференциальной геометрии и топологии, читавшихся автором на механико-математическом факультете МГУ в разные годы. В дополнениях приводятся некоторые сюжеты (связности в расслоениях, теорема Фробениуса, производные Ли и др.), которые были включены в курс в отдельные годы либо содержались в аналогичных курсах лекций в Независимом московском университете.
Для студентов математических и физических специальностей. ...
Added: October 12, 2026
Zykov S. V., Ермаков С. Р., Современные наукоемкие технологии 2026 № 9 С. 43–53
При федеративном обучении с неоднородными клиентскими данными и переменными задержками запоздавшие обновления могут ухудшать качество модели, а обмен параметрами с глобальным сервером увеличивает сетевую нагрузку. Целью исследования является разработка и теоретико-экспериментальное обоснование метода и алгоритмов адаптивного федеративного обучения с учетом распределенного запаздывания клиентских обновлений. Для обоснования разрабатываемых решений использованы событийная и непрерывная модели градиентных обновлений, ...
Added: October 11, 2026
Брычков М. Е., Незнанов А.А., Программирование 2026 № 4 С. 50–66
The matrix profile (MP) quickly became one of the most important time series preprocessing methods when it was introduced in 2016, facilitating the solution of a wide range of time series analysis problems, in particular anomaly and pattern detection problems. The high significance has led to the emergence of various tools for MP calculating, but ...
Added: October 9, 2026
М.: Юрайт, 2026.
The Collection of Olympiad Problems (COP) in Probability Theory and Mathematical Statistics (PTMS) is offered as a teaching aid primarily for university students and faculty as a developmental supplementary resource, expanding the range of problems to be solved in lectures, seminars, and out-of-class independent work with students in various formats, including (as the title suggests) ...
Added: October 9, 2026
Aleskerov F. T., Вайншток А. П., Делахова А. М. et al., Информационные процессы 2026 Т. 26 № 3 С. 895–913
The development and effective management of territorial entities are priority issues for all states, particularly in the context of the digital transformation of public administration. Over the past decade, the integration of information technologies into municipal and regional planning has significantly altered approaches to strategic development, service delivery, and public engagement. This paper describes the ...
Added: October 9, 2026
Kupavskii A., Noskov F., Forum of Mathematics, Sigma 2026 Vol. 14 Article 124
We call a family of $s$ sets $\{F_1, \ldots, F_s\}$ a sunflower with $s$ petals if, for any distinct $i, j \in [s]$, one has $F_i \cap F_j = \cap_{u = 1}^s F_u$. The set $C = \cap_{u = 1}^s F_u$ is called the {\it core} of the sunflower. It is a classical result of ...
Added: October 8, 2026
Stanislav Morozov, Calcolo 2026 Vol. 63 No. 2 Article 23
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
Stanislav Morozov, Zheltkov D., Osinsky A., Russian Journal on Numerical Analysis and Mathematical Modelling 2024 Vol. 39 No. 5 P. 311–328
Nowadays, low-rank approximations are a critical component of many numerical procedures. Traditionally the problem of low-rank approximation of matrices is solved in unitary invariant norms such as Frobenius or spectral norm due to the existence of efficient methods for constructing approximations. However, recent results discover the potential of low-rank approximations in the Chebyshev norm, which ...
Added: February 18, 2026
Guminov S., Dvurechensky P., Tupitsa N. et al., , in: Proceedings of the 38th International Conference on Machine Learning (ICML 2021)Vol. 139.: PMLR, 2021. P. 3886–3898.
Added: October 30, 2022
Ivanova A., Pasechnyuk D., Grishchenko D. et al., , in: Optimization and Applications: 12th International Conference, OPTIMA 2021, Petrovac, Montenegro, September 27 – October 1, 2021, Proceedings.: Switzerland: Springer, 2021. Ch. 268319 P. 20–37.
In this paper, we present a generic framework that allows accelerating almost arbitrary non-accelerated deterministic and randomized algorithms for smooth convex optimization problems. The major approach of our envelope is the same as in Catalyst [37]: an accelerated proximal outer gradient method, which is used as an envelope for a non-accelerated inner method for the ...
Added: October 30, 2022
Tupitsa N., Dvurechensky P., Gasnikov A. et al., Journal of Inverse and Ill-posed problems 2021 Vol. 29 No. 5 P. 721–739
We consider alternating minimization procedures for convex and non-convex optimization problems with the vector of variables divided into several blocks, each block being amenable for minimization with respect to its variables while maintaining other variables' blocks constant. In the case of two blocks, we prove a linear convergence rate for alternating minimization procedure under the ...
Added: September 29, 2021
Tupitsa, N., Dvurechensky P., Gasnikov A. et al., , in: 2020 IEEE 59th Conference on Decision and Control (CDC).: IEEE, 2020. P. 6132–6137.
We study multimarginal optimal transport (MOT) problems, which include, as a particular case, the Wasserstein barycenter problem. In MOT problems, one has to find an optimal coupling between m probability measures, which amounts to finding a tensor of order m. We propose a method based on accelerated alternating minimization and estimate the complexity to find ...
Added: February 5, 2021
Tupitsa N., Gasnikov A., Dvurechensky P. et al., , in: Mathematical Optimization Theory and Operations Research. MOTOR 2020. Communications in Computer and Information ScienceVol. 1275.: Springer, 2020. P. 192–204.
In this paper we experimentally check a hypothesis, that dual problem to discrete entropy regularized optimal transport problem possesses strong convexity on a certain compact set. We present a numerical estimation technique of parameter of strong convexity and show that such an estimate increases the performance of an accelerated alternating minimization algorithm for strongly convex ...
Added: October 28, 2020