FLDA alternates between cheap federated distillation exchanges and full federated learning updates, achieving higher accuracy than either method alone with large energy savings in simulated EH-IoT networks.
Federated learning with fair incentives and robust aggregation for UA V-aided crowdsens- ing,
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Federated Learning-Distillation Alternation for Resource-Constrained IoT
FLDA alternates between cheap federated distillation exchanges and full federated learning updates, achieving higher accuracy than either method alone with large energy savings in simulated EH-IoT networks.