Sadiev, Abdurakhmon

14 publications

NeurIPS 2025 Error Feedback Under $(L_0,L_1)$-Smoothness: Normalization and Momentum Sarit Khirirat, Abdurakhmon Sadiev, Artem Riabinin, Eduard Gorbunov, Peter Richtárik

NeurIPS 2025 Second-Order Optimization Under Heavy-Tailed Noise: Hessian Clipping and Sample Complexity Limits Abdurakhmon Sadiev, Peter Richtárik, Ilyas Fatkhullin

NeurIPSW 2024 Communication-Efficient Algorithms Under Generalized Smoothness Assumptions Sarit Khirirat, Abdurakhmon Sadiev, Artem Riabinin, Eduard Gorbunov, Peter Richtárik

NeurIPSW 2024 Differentially Private Random Block Coordinate Descent Arto Maranjyan, Abdurakhmon Sadiev, Peter Richtárik

NeurIPS 2024 Don't Compress Gradients in Random Reshuffling: Compress Gradient Differences Abdurakhmon Sadiev, Grigory Malinovsky, Eduard Gorbunov, Igor Sokolov, Ahmed Khaled, Konstantin Burlachenko, Peter Richtárik

ICML 2024 High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise Eduard Gorbunov, Abdurakhmon Sadiev, Marina Danilova, Samuel Horváth, Gauthier Gidel, Pavel Dvurechensky, Alexander Gasnikov, Peter Richtárik

NeurIPSW 2024 SPAM: Stochastic Proximal Point Method with Momentum Variance Reduction for Nonconvex Cross-Device Federated Learning Avetik Karagulyan, Egor Shulgin, Abdurakhmon Sadiev, Peter Richtárik

NeurIPSW 2024 Stochastic Proximal Point Methods for Monotone Inclusions Under Expected Similarity Abdurakhmon Sadiev, Laurent Condat, Peter Richtárik

TMLR 2023 AI-SARAH: Adaptive and Implicit Stochastic Recursive Gradient Methods Zheng Shi, Abdurakhmon Sadiev, Nicolas Loizou, Peter Richtárik, Martin Takáč

TMLR 2023 Adaptive Compression for Communication-Efficient Distributed Training Maksim Makarenko, Elnur Gasanov, Abdurakhmon Sadiev, Rustem Islamov, Peter Richtárik

ICMLW 2023 Federated Optimization Algorithms with Random Reshuffling and Gradient Compression Abdurakhmon Sadiev, Grigory Malinovsky, Eduard Gorbunov, Igor Sokolov, Ahmed Khaled, Konstantin Pavlovich Burlachenko, Peter Richtárik

ICML 2023 High-Probability Bounds for Stochastic Optimization and Variational Inequalities: The Case of Unbounded Variance Abdurakhmon Sadiev, Marina Danilova, Eduard Gorbunov, Samuel Horváth, Gauthier Gidel, Pavel Dvurechensky, Alexander Gasnikov, Peter Richtárik

NeurIPS 2022 Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox Abdurakhmon Sadiev, Dmitry Kovalev, Peter Richtarik

NeurIPS 2022 Optimal Algorithms for Decentralized Stochastic Variational Inequalities Dmitry Kovalev, Aleksandr Beznosikov, Abdurakhmon Sadiev, Michael Persiianov, Peter Richtarik, Alexander Gasnikov