S. P. Chebykin, B. I. Prokhorov, A. N. Beznosikov, “Optimization with Markovian noise: towards optimal rates in strong growth case”, Dokl. RAN. Math. Inf. Proc. Upr., 527 (2025), 523–532
2.
G. Chirkov, Yu. Kabikov, D. Medyakov, G. Molodtsov, A. Shestakov, A. Beznosikov, “Extrasaga: variance reduction hybrid method for variational inequalities”, Dokl. RAN. Math. Inf. Proc. Upr., 527 (2025), 415–431
3.
E. D. Petrov, G. V. Evseev, A. V. Antonov, A. S. Veprikov, N. A. Bushkov, S. V. Moiseev, A. N. Beznosikov, “Sampling of semi-orthogonal matrices for the Muon algorithm”, Dokl. RAN. Math. Inf. Proc. Upr., 527 (2025), 217–228
2024
4.
R. E. Voronov, E. M. Maslennikov, A. N. Beznosikov, “Communication-efficient solution of distributed variational inequalities using biased compression, data similarity and local updates”, Computer Research and Modeling, 16:7 (2024), 1813–1827
5.
A. S. Veprikov, E. D. Petrov, G. V. Evseev, A. N. Beznosikov, “Zero order algorithm for decentralised optimization problems”, Dokl. RAN. Math. Inf. Proc. Upr., 520:2 (2024), 295–312; Dokl. Math., 110:suppl. 1 (2024), 261–S277
6.
S. A. Chezhegov, S. N. Skorik, N. Khachaturov, D. S. Shalagin, A. A. Avetisyan, M. Takáč, Y. A. Kholodov, A. N. Beznosikov, “Local methods with adaptivity via scaling”, Uspekhi Mat. Nauk, 79:6(480) (2024), 117–158; Russian Math. Surveys, 79:6 (2024), 1051–1091
7.
A. E. Sadchikov, S. A. Chezhegov, A. N. Beznosikov, A. V. Gasnikov, “Local SGD for near-quadratic problems: Improving convergence under unconstrained noise conditions”, Uspekhi Mat. Nauk, 79:6(480) (2024), 83–116; Russian Math. Surveys, 79:6 (2024), 1017–1049
8.
D. A. Bylinkin, K. D. Degtyarev, A. N. Beznosikov, “Accelerated Stochastic ExtraGradient: Mixing Hessian and gradient similarity to reduce communication in distributed and federated learning”, Uspekhi Mat. Nauk, 79:6(480) (2024), 5–38; Russian Math. Surveys, 79:6 (2024), 939–973
9.
D. O. Medyakov, G. L. Molodtsov, A. N. Beznosikov, “Effective method with compression for distributed and federated cocoercive variational inequalities”, Proceedings of ISP RAS, 36:5 (2024), 93–108
10.
S. S. Ablaev, A. N. Beznosikov, A. V. Gasnikov, D. M. Dvinskikh, A. V. Lobanov, S. M. Puchinin, F. S. Stonyakin, “On some works of Boris Teodorovich Polyak on the convergence of gradient methods and their development”, Zh. Vychisl. Mat. Mat. Fiz., 64:4 (2024), 587–626; Comput. Math. Math. Phys., 64:4 (2024), 635–675
D. Medyakov, G. Molodtsov, A. Beznosikov, A. Gasnikov, “Optimal data splitting in distributed optimization for machine learning”, Dokl. RAN. Math. Inf. Proc. Upr., 514:2 (2023), 343–354; Dokl. Math., 108:suppl. 2 (2023), S465–S475
A. Pichugin, M. Pechin, A. Beznosikov, A. Savchenko, A. Gasnikov, “Optimal analysis of method with batching for monotone stochastic finite-sum variational inequalities”, Dokl. RAN. Math. Inf. Proc. Upr., 514:2 (2023), 212–224; Dokl. Math., 108:suppl. 2 (2023), S348–S359
13.
M. I. Rudakov, A. N. Beznosikov, Y. A. Kholodov, A. V. Gasnikov, “Activations and gradients compression for model-parallel training”, Dokl. RAN. Math. Inf. Proc. Upr., 514:2 (2023), 126–137; Dokl. Math., 108:suppl. 2 (2023), S272–S281
A. N. Beznosikov, A. V. Gasnikov, K. E. Zainullina, A. Yu. Maslovskii, D. A. Pasechnyuk, “A unified analysis of variational inequality methods: variance reduction, sampling, quantization, and coordinate descent”, Zh. Vychisl. Mat. Mat. Fiz., 63:2 (2023), 189–217; Comput. Math. Math. Phys., 63:2 (2023), 147–174
A. I. Bazarova, A. N. Beznosikov, A. V. Gasnikov, “Linearly convergent gradient-free methods for minimization of parabolic approximation”, Computer Research and Modeling, 14:2 (2022), 239–255
G. L. Molodtsov, D. O. Medyakov, S. N. Skorik, N. Khachaturov, Sh. T. Tigranyan, V. I. Aletov, A. A. Avetisyan, M. Takáč, A. N. Beznosikov, “Defending against Byzantine attacks by trust-based weighting of agents”, Uspekhi Mat. Nauk, 80:6(486) (2025), 191–194
