I had the opportunity to contribute to the optimization and machine learning community through the following publications. They are organized by research area:
Publications: 6 NeurIPS, 4 ICML, 2 AISTATS, 2 SICON, 1 JMLR, 1 SIOPT
Large-Scale Optimization
2021
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Peter Richtárik, Igor Sokolov, Ilyas Fatkhullin. EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback, NeurIPS 2021 oral.
▼ Poster
2022
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Peter Richtárik, Igor Sokolov, Ilyas Fatkhullin, Elnur Gasanov, Eduard Gorbunov, Zhize Li. 3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation, ICML 2022 spotlight.
▼ Poster
2023
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Ilyas Fatkhullin, Alexander Tyurin, Peter Richtárik. Momentum Provably Improves Error Feedback!, NeurIPS 2023.
▼ Poster
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Junchi Yang, Xiang Li, Ilyas Fatkhullin, Niao He. Two Sides of One Coin: the Limits of Untuned SGD and the Power of Adaptive Methods, NeurIPS 2023.
Reinforcement Learning and Control
2021
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Ilyas Fatkhullin, Boris Polyak. Optimizing Static Linear Feedback: Gradient Method, SIAM Journal on Control and Optimization, 2021.
2023
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Ilyas Fatkhullin, Anas Barakat, Anastasia Kireeva, Niao He. Stochastic Policy Gradient Methods: Improved Sample Complexity for Fisher-non-degenerate Policies, ICML 2023.
▼ Poster
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Anas Barakat, Ilyas Fatkhullin, Niao He. Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space, ICML 2023.
▼ Poster
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Jiduan Wu, Anas Barakat, Ilyas Fatkhullin, Niao He. Learning Zero-Sum Linear Quadratic Games with Improved Sample Complexity and Last-Iterate Convergence, Accepted for publication at SIAM Journal on Control and Optimization, 2025. Preliminary version appeared at CDC 2023.
2024-2025
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Rustem Islamov, Yarden As, Ilyas Fatkhullin. Safe-EF: Error Feedback for Nonsmooth Constrained Optimization, ICML 2025.
Theoretical Foundations
2022
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Ilyas Fatkhullin*, Jalal Etesami*, Niao He, Negar Kiyavash. Sharp Analysis of Stochastic Optimization under Global Kurdyka-Łojasiewicz Inequality, NeurIPS 2022.
▼ Poster
2023
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Ilyas Fatkhullin, Niao He, Yifan Hu. Stochastic Optimization under Hidden Convexity, Accepted for publication at SIAM Journal on Optimization, 2025. Preliminary version at OptML@NeurIPS 2023.
▼ Poster
2024-2025
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Ilyas Fatkhullin, Niao He. Taming Nonconvex Stochastic Mirror Descent with General Bregman Divergence, AISTATS 2024.
▼ Poster
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Florian Hübler*, Ilyas Fatkhullin*, Niao He. From Gradient Clipping to Normalization for Heavy Tailed SGD, AISTATS 2025.