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cs.LG2025
Communication Compression for Distributed Learning with Aggregate and Server-Guided Feedback
Tomas Ortega, Chun-Yin Huang, Xiaoxiao Li +1
Distributed learning, particularly Federated Learning (FL), faces a significant bottleneck in the communication cost, particularly the uplink transmission of client-to-server updat…
cs.LG2025
Decentralized Parameter-Free Online Learning
Tomas Ortega, Hamid Jafarkhani
We propose the first parameter-free decentralized online learning algorithms with network regret guarantees, which achieve sublinear regret without requiring hyperparameter tuning.…