FedHPro learns hyper-prototypes via gradient matching and mutual-contrastive learning to achieve state-of-the-art performance in heterogeneous federated learning.
Table A1.Results on CIFAR10, CIFAR100, HAM10000, TinyImageNet withLabel Skew
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FedHPro: Federated Hyper-Prototype Learning via Gradient Matching
FedHPro learns hyper-prototypes via gradient matching and mutual-contrastive learning to achieve state-of-the-art performance in heterogeneous federated learning.