FLUDE combines dependability-aware device selection, local model caching, and stale-aware model distribution to make federated learning faster, more accurate, and more efficient when many devices are unreliable.
Federated learning for generalization, robustness, fairness: A survey and benchmark
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A Robust Federated Learning Framework for Undependable Devices at Scale
FLUDE combines dependability-aware device selection, local model caching, and stale-aware model distribution to make federated learning faster, more accurate, and more efficient when many devices are unreliable.