| Inexact model: A framework for optimization and variational inequalities F Stonyakin, A Tyurin, A Gasnikov, P Dvurechensky, A Agafonov, ... Optimization Methods and Software 36 (6), 1155-1201, 2021 | 70 | 2021 |
| Gradient methods for problems with inexact model of the objective FS Stonyakin, D Dvinskikh, P Dvurechensky, A Kroshnin, O Kuznetsova, ... Mathematical Optimization Theory and Operations Research: 18th International …, 2019 | 61 | 2019 |
| Adaptive catalyst for smooth convex optimization A Ivanova, D Pasechnyuk, D Grishchenko, E Shulgin, A Gasnikov, ... International Conference on Optimization and Applications, 20-37, 2021 | 37 | 2021 |
| Accelerated meta-algorithm for convex optimization problems AV Gasnikov, DM Dvinskikh, PE Dvurechensky, DI Kamzolov, ... Computational Mathematics and Mathematical Physics 61, 17-28, 2021 | 26 | 2021 |
| Oracle complexity separation in convex optimization A Ivanova, P Dvurechensky, E Vorontsova, D Pasechnyuk, A Gasnikov, ... Journal of Optimization Theory and Applications 193 (1), 462-490, 2022 | 21 | 2022 |
| A Damped Newton Method Achieves Global and Local Quadratic Convergence Rate S Hanzely, D Kamzolov, D Pasechnyuk, A Gasnikov, P Richtárik, M Takác Advances in Neural Information Processing Systems 35, 25320-25334, 2022 | 20 | 2022 |
| Inexact Relative Smoothness and Strong Convexity for Optimization and Variational Inequalities by Inexact Model F Stonyakin, A Tyurin, A Gasnikov, P Dvurechensky, A Agafonov, ... arXiv preprint arXiv:2001.09013, 2020 | 19 | 2020 |
| Solving strongly convex-concave composite saddle point problems with a small dimension of one of the variables E Gladin, I Kuruzov, F Stonyakin, D Pasechnyuk, M Alkousa, A Gasnikov arXiv preprint arXiv:2010.02280, 2020 | 14 | 2020 |
| A unified analysis of variational inequality methods: Variance reduction, sampling, quantization, and coordinate descent AN Beznosikov, AV Gasnikov, KE Zainullina, AY Maslovskii, ... Computational Mathematics and Mathematical Physics 63 (2), 147-174, 2023 | 9 | 2023 |
| Non-convex optimization in digital pre-distortion of the signal D Pasechnyuk, A Maslovskiy, A Gasnikov, A Anikin, A Rogozin, A Gornov, ... arXiv preprint arXiv:2103.10552, 2021 | 9* | 2021 |
| One Method for Minimization a Convex Lipschitz-Continuous Function of 2 Variables on a Fixed Square DA Pasechnyuk, FS Stonyakin arXiv preprint arXiv:1812.10300, 2018 | 8* | 2018 |
| Primal-dual gradient methods for searching network equilibria in combined models with nested choice structure and capacity constraints M Kubentayeva, D Yarmoshik, M Persiianov, A Kroshnin, E Kotliarova, ... Computational Management Science 21 (1), 15, 2024 | 7 | 2024 |
| Gradient-type adaptive methods for relatively Lipschitz convex optimization problems F Stonyakin, A Titov, M Alkousa, O Savchuk, D Pasechnyuk arXiv preprint.—2021b.—https://arxiv. org/pdf/2107.05765, 2021 | 7 | 2021 |
| Adaptive mirror descent for the network utility maximization problem A Ivanova, F Stonyakin, D Pasechnyuk, E Vorontsova, A Gasnikov IFAC-PapersOnLine 53 (2), 7851-7856, 2020 | 6 | 2020 |
| Numerical methods for the resource allocation problem in networks A Ivanova, D Pasechnyuk, P Dvurechensky, A Gasnikov, E Vorontsova arXiv preprint arXiv:1909.13321, 2019 | 4 | 2019 |
| Adaptive variant of the Frank–Wolfe algorithm for convex optimization problems GV Aivazian, FS Stonyakin, DA Pasechnyk, MS Alkousa, AM Raigorodsky, ... Programming and Computer Software 49 (6), 493-504, 2023 | 3 | 2023 |
| Upper bounds on maximum admissible noise in zeroth-order optimisation DA Pasechnyuk, A Lobanov, A Gasnikov arXiv preprint arXiv:2306.16371, 2023 | 3 | 2023 |
| Numerical methods for the resource allocation problem in a computer network EA Vorontsova, AV Gasnikov, PE Dvurechensky, AS Ivanova, ... Computational Mathematics and Mathematical Physics 61, 297-328, 2021 | 3 | 2021 |
| Algorithms for Euclidean-Regularised Optimal Transport DA Pasechnyuk, M Persiianov, P Dvurechensky, A Gasnikov International Conference on Optimization and Applications, 84-98, 2023 | 2 | 2023 |
| Convergence analysis of stochastic gradient descent with adaptive preconditioning for non-convex and convex functions DA Pasechnyuk, A Gasnikov, M Takáč arXiv preprint arXiv:2308.14192, 2023 | 2 | 2023 |
Alexander GasnikovMIPTVerified email at mipt.ru
