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cs.LG2024
MARINA-P: Superior Performance in Non-smooth Federated Optimization with Adaptive Stepsizes
Igor Sokolov, Peter Richtárik
Non-smooth communication-efficient federated optimization is crucial for many machine learning applications, yet remains largely unexplored theoretically. Recent advancements have…
cs.LG2024
Cohort Squeeze: Beyond a Single Communication Round per Cohort in Cross-Device Federated Learning
Kai Yi, Timur Kharisov, Igor Sokolov +1
Virtually all federated learning (FL) methods, including FedAvg, operate in the following manner: i) an orchestrating server sends the current model parameters to a cohort of clien…