Learning to Sync at the Edge: Client-Side Adaptive Synchronization for Federated Learning
The scalability and performance of edge federated learning are fundamentally constrained by synchronization bottlenecks. Clients operate under heterogeneous compute, time-varying communication conditions, and, in some settings, privacy constraints, yet synchronization is often still handled with fixed schedules. Howeve...
Ebasa Temesgen, Ammar Ahmed, N. Lechamo et al.
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