Suivre
Eduard Gorbunov
Eduard Gorbunov
Autres nomsЭдуард Александрович Горбунов, Eduard A. Gorbunov
Research Scientist, Mohamed bin Zayed University of Artificial Intelligence
Adresse e-mail validée de mbzuai.ac.ae - Page d'accueil
Titre
Citée par
Citée par
Année
Distributed learning with compressed gradient differences
K Mishchenko, E Gorbunov, M Takáč, P Richtárik
Optimization Methods and Software, 1-16, 2024
2532024
A unified theory of SGD: Variance reduction, sampling, quantization and coordinate descent
E Gorbunov, F Hanzely, P Richtárik
International Conference on Artificial Intelligence and Statistics, 680-690, 2020
1802020
Stochastic optimization with heavy-tailed noise via accelerated gradient clipping
E Gorbunov, M Danilova, A Gasnikov
Advances in Neural Information Processing Systems 33, 15042-15053, 2020
1542020
MARINA: Faster non-convex distributed learning with compression
E Gorbunov, KP Burlachenko, Z Li, P Richtárik
International Conference on Machine Learning, 3788-3798, 2021
1392021
Local SGD: Unified theory and new efficient methods
E Gorbunov, F Hanzely, P Richtárik
International Conference on Artificial Intelligence and Statistics, 3556-3564, 2021
1302021
Recent theoretical advances in non-convex optimization
M Danilova, P Dvurechensky, A Gasnikov, E Gorbunov, S Guminov, ...
High-Dimensional Optimization and Probability: With a View Towards Data …, 2022
1132022
Extragradient method: O (1/k) last-iterate convergence for monotone variational inequalities and connections with cocoercivity
E Gorbunov, N Loizou, G Gidel
International Conference on Artificial Intelligence and Statistics, 366-402, 2022
1042022
Linearly converging error compensated SGD
E Gorbunov, D Kovalev, D Makarenko, P Richtárik
Advances in Neural Information Processing Systems 33, 20889-20900, 2020
932020
Near Optimal Methods for Minimizing Convex Functions with Lipschitz -th Derivatives
A Gasnikov, P Dvurechensky, E Gorbunov, E Vorontsova, ...
Conference on Learning Theory, 1392-1393, 2019
882019
Optimal decentralized distributed algorithms for stochastic convex optimization
E Gorbunov, D Dvinskikh, A Gasnikov
arXiv preprint arXiv:1911.07363, 2019
802019
Optimal tensor methods in smooth convex and uniformly convexoptimization
A Gasnikov, P Dvurechensky, E Gorbunov, E Vorontsova, ...
Conference on Learning Theory, 1374-1391, 2019
79*2019
An accelerated method for derivative-free smooth stochastic convex optimization
E Gorbunov, P Dvurechensky, A Gasnikov
SIAM Journal on Optimization 32 (2), 1210-1238, 2022
73*2022
Stochastic gradient descent-ascent: Unified theory and new efficient methods
A Beznosikov, E Gorbunov, H Berard, N Loizou
International conference on artificial intelligence and statistics, 172-235, 2023
672023
Stochastic three points method for unconstrained smooth minimization
EH Bergou, E Gorbunov, P Richtarik
SIAM Journal on Optimization 30 (4), 2726-2749, 2020
612020
Last-iterate convergence of optimistic gradient method for monotone variational inequalities
E Gorbunov, A Taylor, G Gidel
Advances in neural information processing systems 35, 21858-21870, 2022
582022
EF21 with bells & whistles: Practical algorithmic extensions of modern error feedback
I Fatkhullin, I Sokolov, E Gorbunov, Z Li, P Richtárik
arXiv preprint arXiv:2110.03294, 2021
582021
High-probability bounds for stochastic optimization and variational inequalities: the case of unbounded variance
A Sadiev, M Danilova, E Gorbunov, S Horváth, G Gidel, P Dvurechensky, ...
ICML 2023 [arXiv:2302.00999], 2023
552023
Stochastic extragradient: General analysis and improved rates
E Gorbunov, H Berard, G Gidel, N Loizou
International Conference on Artificial Intelligence and Statistics, 7865-7901, 2022
512022
An accelerated directional derivative method for smooth stochastic convex optimization
P Dvurechensky, E Gorbunov, A Gasnikov
European Journal of Operational Research 290 (2), 601-621, 2021
502021
High-Probability Complexity Bounds for Non-smooth Stochastic Convex Optimization with Heavy-Tailed Noise
E Gorbunov, M Danilova, I Shibaev, P Dvurechensky, A Gasnikov
Journal of Optimization Theory and Applications, 1-60, 2024
48*2024
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