Publications

Eduard Gorbunov, Abdurakhmon Sadiev, Marina Danilova, Samuel Horváth, Gauthier Gidel, Pavel Dvurechensky, Alexander Gasnikov, Peter Richtárik (2023). High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise. arXiv preprint arXiv:2310.01860.

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Abdurakhmon Sadiev, Marina Danilova, Eduard Gorbunov, Samuel Horváth, Gauthier Gidel, Pavel Dvurechensky, Alexander Gasnikov, Peter Richtárik (2023). High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance. arXiv preprint arXiv:2302.00999.

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Maksim Makarenko, Elnur Gasanov, Rustem Islamov, Abdurakhmon Sadiev, Peter Richtárik (2022). Adaptive Compression for Communication-Efficient Distributed Training. arXiv preprint arXiv:2211.00188.

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Abdurakhmon Sadiev, Dmitry Kovalev, Peter Richárik (2022). Communication acceleration of local gradient methods via an accelerated primal-dual algorithm with inexact prox. Advances in Neural Information Processing Systems 35 (NeurIPS 2022).

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Abdurakhmon Sadiev, Grigory Malinovsky, Eduard Gorbunov, Igor Sokolov, Ahmed Khaled, Konstantin Burlachenko, Peter Richtárik (2022). Federated Optimization Algorithms with Random Reshuffling and Gradient Compression. arXiv preprint arXiv:2206.07021.

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Abdurakhmon Sadiev, Aleksandr Beznosikov, Abdulla Jasem Almansoori, Dmitry Kamzolov, Rachael Tappenden, Martin Takáč (2022). Stochastic gradient methods with preconditioned updates. arXiv preprint arXiv:2206.00285.

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Mohammad Alkousa, Alexander Gasnikov, Pavel Dvurechensky, Abdurakhmon Sadiev, Lama Razouk (2022). An Approach for Non-convex Uniformly Concave Structured Saddle Point Problem. Computer Research and Modeling.

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Dmitry Kovalev, Aleksandr Beznosikov, Abdurakhmon Sadiev, Michael Persiianov, Peter Richtárik, Alexander Gasnikov (2022). Optimal algorithms for decentralized stochastic variational inequalities. Advances in Neural Information Processing Systems 35 (NeurIPS 2022).

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Abdurakhmon Sadiev, Ekaterina Borodich, Aleksandr Beznosikov, Darina Dvinskikh, Saveliy Chezhegov, Rachael Tappenden, Martin Takáč, Alexander Gasnikov (2022). Decentralized personalized federated learning: Lower bounds and optimal algorithm for all personalization modes. EURO Journal on Computational Optimization.

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Zheng Shi, Abdurakhmon Sadiev, Nicolas Loizou, Peter Richtárik, Martin Takáč (2022). AI-SARAH: Adaptive and Implicit Stochastic Recursive Gradient Methods. arXiv preprint arXiv:2102.09700.

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Ekaterina Borodich, Aleksandr Beznosikov, Abdurakhmon Sadiev, Vadim Sushko, Nikolay Savelyev, Martin Takáč, Alexander Gasnikov (2021). Decentralized personalized federated min-max problems. arXiv preprint arXiv:2106.07289.

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Abdurakhmon Sadiev, Aleksandr Beznosikov, Pavel Dvurechensky, Alexander Gasnikov (2021). Zeroth-order algorithms for smooth saddle-point problems. Mathematical Optimization Theory and Operations Research: Recent Trends: 20th International Conference, MOTOR 2021, Irkutsk, Russia, July 5–10, 2021, Revised Selected Papers 20.

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Egor Gladin, Abdurakhmon Sadiev, Alexander Gasnikov, Pavel Dvurechensky, Aleksandr Beznosikov, Mohammad Alkousa (2021). Solving smooth min-min and min-max problems by mixed oracle algorithms. Mathematical Optimization Theory and Operations Research: Recent Trends: 20th International Conference, MOTOR 2021, Irkutsk, Russia, July 5–10, 2021, Revised Selected Papers 20.

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Aleksandr Beznosikov, Abdurakhmon Sadiev, Alexander Gasnikov (2020). Gradient-free methods with inexact oracle for convex-concave stochastic saddle-point problem. Mathematical Optimization Theory and Operations Research: 19th International Conference, MOTOR 2020, Novosibirsk, Russia, July 6–10, 2020, Revised Selected Papers 19.

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