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High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise.

, , , , , , , and . CoRR, (2023)

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Partially Personalized Federated Learning: Breaking the Curse of Data Heterogeneity., , , and . CoRR, (2023)Handling Data Heterogeneity via Architectural Design for Federated Visual Recognition., , , and . CoRR, (2023)Federated Learning with Regularized Client Participation., , , and . CoRR, (2023)Better Methods and Theory for Federated Learning: Compression, Client Selection and Heterogeneity.. King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, (2022)base-search.net (ftkingabdullahun:oai:repository.kaust.edu.sa:10754/679634).FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout., , , , , and . NeurIPS, page 12876-12889. (2021)FLIX: A Simple and Communication-Efficient Alternative to Local Methods in Federated Learning., , , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 11374-11421. PMLR, (2022)Enhancing Policy Gradient with the Polyak Step-Size Adaption., , , , , , and . CoRR, (2024)Decentralized Personalized Federated Learning., , and . CoRR, (2024)Maestro: Uncovering Low-Rank Structures via Trainable Decomposition., , , and . ICML, OpenReview.net, (2024)FL_PyTorch: optimization research simulator for federated learning., , and . DistributedML@CoNEXT, page 1-7. ACM, (2021)