FedADP unifies heterogeneous client models in federated learning by dynamically morphing them to a common architecture for aggregation, reporting accuracy improvements of up to 23.3% over FlexiFed.
Adaptive federated learning in resource constrained edge computing systems
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FedADP: Unified Model Aggregation for Federated Learning with Heterogeneous Model Architectures
FedADP unifies heterogeneous client models in federated learning by dynamically morphing them to a common architecture for aggregation, reporting accuracy improvements of up to 23.3% over FlexiFed.