Ilyas Fatkhullin
Cited by
Cited by
EF21: A new, simpler, theoretically better, and practically faster error feedback
P Richtárik, I Sokolov, I Fatkhullin
Advances in Neural Information Processing Systems 34, 4384-4396, 2021
Optimizing static linear feedback: Gradient method
I Fatkhullin, B Polyak
SIAM Journal on Control and Optimization 59 (5), 3887-3911, 2021
EF21 with bells & whistles: Practical algorithmic extensions of modern error feedback
I Fatkhullin, I Sokolov, E Gorbunov, Z Li, P Richtárik
OptML Workshop at NeurIPS 2021, 2021
3PC: Three point compressors for communication-efficient distributed training and a better theory for lazy aggregation
P Richtárik, I Sokolov, E Gasanov, I Fatkhullin, Z Li, E Gorbunov
International Conference on Machine Learning, 18596-18648, 2022
Stochastic policy gradient methods: Improved sample complexity for fisher-non-degenerate policies
I Fatkhullin, A Barakat, A Kireeva, N He
International Conference on Machine Learning 40, 9827-9869, 2023
Sharp analysis of stochastic optimization under global Kurdyka-Lojasiewicz inequality
I Fatkhullin, J Etesami, N He, N Kiyavash
Advances in Neural Information Processing Systems 35, 15836-15848, 2022
Two sides of one coin: the limits of untuned sgd and the power of adaptive methods
J Yang, X Li, I Fatkhullin, N He
Advances in Neural Information Processing Systems 36, 2024
Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space
A Barakat, I Fatkhullin, N He
International Conference on Machine Learning 40, 1753-1800, 2023
Momentum Provably Improves Error Feedback!
I Fatkhullin, A Tyurin, P Richtárik
37th Conference on Neural Information Processing Systems (NeurIPS 2023), 2023
Stochastic Optimization under Hidden Convexity
I Fatkhullin, N He, Y Hu
arXiv preprint arXiv:2401.00108, 2023
Learning Zero-Sum Linear Quadratic Games with Improved Sample Complexity
J Wu, A Barakat, I Fatkhullin, N He
IEEE Conference on Decision and Control 62, 2023
Use of projective coordinate descent in the fekete problem
BT Polyak, IF Fatkhullin
Computational Mathematics and Mathematical Physics 60 (5), 795-807, 2020
Taming Nonconvex Stochastic Mirror Descent with General Bregman Divergence
I Fatkhullin, N He
AISTATS 2024, 2024
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