A temporal-drift and collective-divergence aware greedy client scheduler plus bandwidth allocator accelerates convergence in federated edge learning with streaming, non-i.i.d. data.
Fairness-Aware Client Selection in Federated Learning with Heterogeneous Data and Resources,
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FedTeddi: Temporal Drift and Divergence Aware Scheduling for Timely Federated Edge Learning
A temporal-drift and collective-divergence aware greedy client scheduler plus bandwidth allocator accelerates convergence in federated edge learning with streaming, non-i.i.d. data.