Агафонов Артем Дмитриевич

Artem Agafonov, Dmitry Kamzolov, Rachael Tappenden, Alexander Gasnikov, Martin Takáč. Flecs: A federated learning second-order framework via compression and sketching (2025) Optimization Methods and Software Q2

Artem Agafonov, Vladislav Ryspayev, Samuel Horváth, Alexander Gasnikov, Martin Takáč, Slavomir Hanzely. Simple Stepsize for Quasi-Newton Methods with Global Convergence Guarantees (2025) arXiv preprint arXiv:2508.19712

Artem Agafonov, Dmitry Kamzolov, Alexander Gasnikov, Ali Kavis, Kimon Antonakopoulos, Volkan Cevher, Martin Takáč. Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness (2024) Scopus DOI A*

Artem Agafonov, Petr Ostroukhov, Roman Mozhaev, Konstantin Yakovlev, Eduard Gorbunov, Martin Takác, Alexander Gasnikov, Dmitry Kamzolov. Exploring jacobian inexactness in second-order methods for variational inequalities: lower bounds, optimal algorithms and quasi-newton approximations (2024) Advances in Neural Information Processing Systems A*

Dmitry Kamzolov, Dmitry Pasechnyuk, Artem Agafonov, Alexander Gasnikov, Martin Takáč. Optami: Global superlinear convergence of high-order methods (2024) A*

Agafonov, A., Kamzolov, D., Dvurechensky, P., Gasnikov, A., Takáč, M. Inexact tensor methods and their application to stochastic convex optimization (2024) Optimization Methods and Software, 39 (1), pp. 42-83. Scopus DOI Q1

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

Agafonov, A., Dvurechensky, P., Scutari, G., Gasnikov, A., Kamzolov, D., Lukashevich, A., Daneshmand, A. An Accelerated Second-Order Method for Distributed Stochastic Optimization (2021) Proceedings of the IEEE Conference on Decision and Control, 2021-December, pp. 2407-2413. Scopus WOS DOI

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