Adaptive Catalyst for Smooth Convex Optimization

A. Ivanova; Pasechnyuk D.; Grishchenko D.; Shulgin E.; A. Gasnikov; Matyukhin V.

doi:10.1007/978-3-030-91059-4_2

Публикации

?

Adaptive Catalyst for Smooth Convex Optimization

Ch. 268319. P. 20–37.

Иванова А. С., Pasechnyuk D., Grishchenko D., Shulgin E., Гасников А. В., Matyukhin V.

Язык: английский

DOI

Текст на другом сайте

Ключевые слова: Alternating minimization Adaptive Methods Accelerated methods Catalyst Coordinate descent Distributed methods

В книге

Optimization and Applications: 12th International Conference, OPTIMA 2021, Petrovac, Montenegro, September 27 – October 1, 2021, Proceedings

Switzerland: Springer, 2021.

Analysis of the alternating minimization method for low-rank canonical polyadic decomposition in the Chebyshev norm

Морозов С. В., Calcolo 2026 Vol. 63 No. 2 Article 23

Добавлено: 22 мая 2026 г.

Refining uniform approximation algorithm for low-rank Chebyshev embeddings

Stanislav Morozov, Zheltkov D., Osinsky A., Russian Journal on Numerical Analysis and Mathematical Modelling 2024 Vol. 39 No. 5 P. 311–328

Добавлено: 18 февраля 2026 г.

Green and Selective Oxidation of Benzyl Alcohol to Benzaldehyde over Transition Metal LDH Nanosheets: Combining Experiments and DFT Calculations

Mehrabi-Kalajahi S., Vasigh S. A., Wu X. и др., The Journal of Physical Chemistry Letters 2025 Vol. 16 No. 46 P. 12113–12123

Добавлено: 22 ноября 2025 г.

Incorporation of Manganese (II) in Beta-Tricalcium Phosphate from EPR and ENDOR Measurements for Powders

Murzakhanov F., Forysenkova Anna A., Fadeeva I. и др., Ceramics 2022 Vol. 5 No. 3 P. 318–329

Добавлено: 12 августа 2025 г.

On the optimal rank-1 approximation of matrices in the Chebyshev norm

Stanislav Morozov, Smirnov M., Zamarashkin N., Linear Algebra and its Applications 2023 Vol. 679 P. 4–29

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 ...

Добавлено: 10 апреля 2025 г.

Decentralized saddle point problems via non-Euclidean mirror prox

Rogozin A., Безносиков А. Н., Двинских Д. М. и др., Optimization Methods and Software 2025 Vol. 40 No. 5 P. 1127–1152

Добавлено: 26 марта 2024 г.

Cationic [TiCl6]+2 and anionic [TiCl6-xLx]-(2-x) titanium complexes with crown ether as pre-catalyst for ethylene polymerization

Gagieva S., Kurmaev D., Magomedov K. и др., European Polymer Journal 2022 Vol. 180 Article 111611

Добавлено: 31 января 2023 г.

Palladium Nanoparticles Entrapped In a Hydrogen Bonded Crystalline Organic Salt Matrix as a Selective Heterogeneous Reduction Catalyst

Kuznetsova S., Yunusov S., Gak A. и др., ChemistrySelect 2022 Vol. 7 No. 41 Article e202203011

Добавлено: 31 января 2023 г.

On a Combination of Alternating Minimization and Nesterov’s Momentum

Guminov S., Двуреченский П. Е., Тупица Н. К. и др., , in: Proceedings of the 38th International Conference on Machine Learning (ICML 2021)Vol. 139.: PMLR, 2021. P. 3886–3898.

Добавлено: 30 октября 2022 г.

Synthesis and characterization of Pt-HxMoO3 catalysts for CO-tolerant PEMFCs

Kurdin K., Kuznetsov V., Vitaly V. Sinitsyn и др., Catalysis Today 2022 Vol. 388-389 P. 147–157

Добавлено: 16 сентября 2022 г.

Alternating minimization methods for strongly convex optimization

Тупица Н. К., Двуреченский П. Е., Гасников А. В. и др., Journal of Inverse and Ill-posed problems 2021 Vol. 29 No. 5 P. 721–739

Добавлено: 29 сентября 2021 г.

Multimarginal Optimal Transport by Accelerated Alternating Minimization

Tupitsa, N., Двуреченский П. Е., Гасников А. В. и др., , in: 2020 IEEE 59th Conference on Decision and Control (CDC).: IEEE, 2020. P. 6132–6137.

Добавлено: 5 февраля 2021 г.

On Some Methods for Strongly Convex Optimization Problems with One Functional Constraint

Stonyakin F. S., Алкуса М., Титов А. А. и др., , in: Mathematical Optimization Theory and Operations Research, 18th International Conference, MOTOR 2019 Ekaterinburg, Russia, July 8–12, 2019Vol. 11548.: Springer, 2019. P. 82–96.

Добавлено: 29 октября 2020 г.

Strongly Convex Optimization for the Dual Formulation of Optimal Transport

Tupitsa N., Гасников А. В., Двуреченский П. Е. и др., , in: Mathematical Optimization Theory and Operations Research. MOTOR 2020. Communications in Computer and Information ScienceVol. 1275.: Springer, 2020. P. 192–204.

Добавлено: 28 октября 2020 г.

Convergence of an alternating maximization procedure

Andresen A., Спокойный В. Г., Journal of Machine Learning Research 2016 No. 17(63) P. 1–53

We derive two convergence results for a sequential alternating maximization procedure to approximate the maximizer of random functionals such as the realized log likelihood in MLE estimation. We manage to show that the sequence attains the same deviation properties as shown for the profile M-estimator by Andresen and Spokoiny (2013), that means a finite sample ...

Добавлено: 8 сентября 2016 г.