Stonyakin Fedor Sergeevich

Ilya Kuruzov, Mohammad Alkousa, Fedor Stonyakin, Alexander Gasnikov. Gradient-type methods for decentralized optimization problems with Polyak–Łojasiewicz condition over time-varying networks (2025) Optimization Methods and Software, 1–28. DOI Q2

Artem Vasin, Valery Krivchenko, Dmitry Kovalev, Fedyor Stonyakin, Nazari Tupitsa, Pavel Dvurechensky, Mohammad Alkousa, Nikita Kornilov, Alexander Gasnikov. On Solving Minimization and Min-Max Problems by First-Order Methods with Relative Error in Gradients (2025) 

Alkousa, M., Stonyakin, F., Gasnikov, A., Abdo, A., Alcheikh, M. Higher degree inexact model for optimization problems (2024) Chaos, Solitons and Fractals, 186, статья № 115292, . Scopus DOI Q1

Klimza, A., Gasnikov, A., Stonyakin, F., Alkousa, M. Universal methods for variational inequalities: Deterministic and stochastic cases (2024) Chaos, Solitons and Fractals, 187, статья № 115418, . Scopus DOI Q1

Gasnikov, A.V., Alkousa, M.S., Lobanov, A.V., Dorn, Y.V., Stonyakin, F.S., Kuruzov, I.A., Singh, S.R. On Quasi-Convex Smooth Optimization Problems by a Comparison Oracle (2024) Russian Journal of Nonlinear Dynamics, 20 (5), pp. 813-825. Scopus DOI Q3

Gasnikov, A.V., Lobanov, A.V., Stonyakin, F.S. Highly Smooth Zeroth-Order Methods for Solving Optimization Problems under the PL Condition (2024) Computational Mathematics and Mathematical Physics, 64 (4), pp. 739-770. Scopus DOI Q3

Ablaev, S.S., Beznosikov, A.N., Gasnikov, A.V., Dvinskikh, D.M., Lobanov, A.V., Puchinin, S.M., Stonyakin, F.S. On Some Works of Boris Teodorovich Polyak on the Convergence of Gradient Methods and Their Development (2024) Computational Mathematics and Mathematical Physics, 64 (4), pp. 635-675. Scopus DOI Q3

Savchuk, O., Puchinin, S., Stonyakin, F., Alkousa, M., Gasnikov, A. Numerical Methods for Variational Inequalities and Saddle Point Problems with Relative Inexact Information (2024) Communications in Computer and Information Science, 2239 CCIS, pp. 19-45. Scopus DOI Q4

O. S. Savchuk, M. S. Alkousa, A. S. Shushko, A. A. Vyguzov, F. S. Stonyakin, D. A. Pasechnyuk, A. V. Gasnikov. Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems (2024)

Stonyakin F., Kuruzov I., Polyak B. Stopping Rules for Gradient Methods for Non-convex Problems with Additive Noise in Gradient (2023) Journal of Optimization Theory and Applications, 198 (2), pp. 531 - 551 Scopus DOI Q1

Ablaev S.S., Stonyakin F.S., Alkousa M.S., Pasechnyk D.A. Adaptive Methods for Variational Inequalities with Relatively Smooth and Reletively Strongly Monotone Operators (2023) Programming and Computer Software, 49 (6), pp. 485 - 492 Scopus DOI Q3

Ablaev, S.S., Stonyakin, F.S., Alkousa, M.S., Gasnikov, A.V. Adaptive Subgradient Methods for Mathematical Programming Problems with Quasiconvex Functions (2023) Proceedings of the Steklov Institute of Mathematics, 323, pp. S1-S18. Scopus DOI Q3

Savchuk, O., Stonyakin, F., Alkousa, M., Zabirova, R., Titov, A., Gasnikov, A. Online Optimization Problems with Functional Constraints Under Relative Lipschitz Continuity and Relative Strong Convexity Conditions (2023) Communications in Computer and Information Science, 1881 CCIS, pp. 29-43. Scopus DOI Q4

Stonyakin F.S., Ablaev S.S., Baran I.V., Alkousa M.S. Subgradient methods for weakly convex and relatively weakly convex problems with a sharp minimum (2023) Сomputer Research and Modeling, 15 (2), pp. 393 - 412 Scopus DOI Q4

Ablaev, S.S., Stonyakin, F.S., Alkousa, M.S., Gasnikov, A.V. Adaptive subgradient methods for mathematical programming problems with quasi-convex functions (2023) Trudy Instituta Matematiki i Mekhaniki UrO RAN, 29 (3), pp. 7-25. Scopus DOI

Stonyakin, F., Alkousa, M., Titov, A., Savchuk, O., Gasnikov, A. Adaptive algorithms for relatively lipschitz continuous convex optimization problems (2023) Pure and Applied Functional Analysis, 8 (5), pp. 1505-1526. Scopus

Stonyakin F. , Gasnikov A. , Dvurechensky P. , Titov A. , Alkousa M. Generalized Mirror Prox Algorithm for Monotone Variational Inequalities: Universality and Inexact Oracle // Journal of Optimization Theory and Applications, Vol. 194, No. 3, P. 988 - 1013 Scopus WOS DOI Q1

Ablaev, S.S., Titov, A.A., Stonyakin, F.S., Alkousa, M.S., Gasnikov, A. Some Adaptive First-Order Methods for Variational Inequalities with Relatively Strongly Monotone Operators and Generalized Smoothness (2022) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13781 LNCS, pp. 135-150. Scopus WOS DOI Q2

Stonyakin, F., Tyurin, A., Gasnikov, A., Dvurechensky, P., Agafonov, A., Dvinskikh, D., Alkousa, M., Pasechnyuk, D., Artamonov, S., Piskunova, V. Inexact model: a framework for optimization and variational inequalities (2021) Optimization Methods and Software, 36 (6), pp. 1155-1201. Scopus DOI Q1

Titov, A.A., Stonyakin, F.S., Alkousa, M.S., Gasnikov, A.V. Algorithms for Solving Variational Inequalities and Saddle Point Problems with Some Generalizations of Lipschitz Property for Operators (2021) Communications in Computer and Information Science, 1476 CCIS, pp. 86-101. Scopus DOI Q4

Alkousa, M.S., Gasnikov, A.V., Dvinskikh, D.M., Kovalev, D.A., Stonyakin, F.S. Accelerated Methods for Saddle-Point Problem (2020) Computational Mathematics and Mathematical Physics, 60 (11), pp. 1787-1809. Scopus DOI Q2

Ivanova, A., Stonyakin, F., Pasechnyuk, D., Vorontsova, E., Gasnikov, A. Adaptive mirror descent for the network utility maximization problem (2020) IFAC-PapersOnLine, 53, pp. 7851-7856. Scopus WOS DOI Q3

Titov, A.A., Stonyakin, F.S., Alkousa, M.S., Ablaev, S.S., Gasnikov, A.V. Analogues of Switching Subgradient Schemes for Relatively Lipschitz-Continuous Convex Programming Problems (2020) Communications in Computer and Information Science, 1275 CCIS, pp. 133-149. Scopus WOS DOI Q4

Stonyakin, F.S., Stepanov, A.N., Gasnikov, A.V., Titov, A.A. Mirror descent for constrained optimization problems with large subgradient values of functional constraints [Метод зеркального спуска для условных задач оптимизации с большими значениями норм субградиентов функциональных ограничений] (2020) Computer Research and Modeling, 12 (2), pp. 301-317. Scopus DOI Q4

Dvurechensky, P.E., Gasnikov, A.V., Nurminski, E.A., Stonyakin, F.S. Advances in low-memory subgradient optimization (2020) Numerical Nonsmooth Optimization: State of the Art Algorithms, pp. 19-59. Scopus DOI

Gasnikov, A.V., Dvurechensky, P.E., Stonyakin, F.S., Titov, A.A. An Adaptive Proximal Method for Variational Inequalities (2019) Computational Mathematics and Mathematical Physics, 59 (5), pp. 836-841. Scopus DOI Q2

Stonyakin, F.S., Dvinskikh, D., Dvurechensky, P., Kroshnin, A., Kuznetsova, O., Agafonov, A., Gasnikov, A., Tyurin, A., Uribe, C.A., Pasechnyuk, D., Artamonov, S. Gradient methods for problems with inexact model of the objective (2019) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11548 LNCS, pp. 97-114. Scopus DOI Q3

Titov, A.A., Stonyakin, F.S., Gasnikov, A.V., Alkousa, M.S. Mirror descent and constrained online optimization problems (2019) Communications in Computer and Information Science, 974, pp. 64-78. Scopus DOI Q4

Bayandina, A., Dvurechensky, P., Gasnikov, A., Stonyakin, F., Titov, A. Mirror descent and convex optimization problems with non-smooth inequality constraints (2018) Lecture Notes in Mathematics, 2227, pp. 181-213. Scopus DOI Q4