A co-distillation federated learning variant sharing majority-class feature averages is reported to keep minority-class accuracy higher than FedAvg, FedProto, FedAMP, and FedDistill on two medical imaging datasets under class skew.
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Framework for Co-distillation Driven Federated Learning to Address Class Imbalance in Healthcare
A co-distillation federated learning variant sharing majority-class feature averages is reported to keep minority-class accuracy higher than FedAvg, FedProto, FedAMP, and FedDistill on two medical imaging datasets under class skew.