FedRIR improves personalized federated learning by separating client-specific and global features with masked reconstruction and mutual information minimization, achieving up to 3.93% higher accuracy than prior methods.
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FedRIR: Rethinking Information Representation in Federated Learning
FedRIR improves personalized federated learning by separating client-specific and global features with masked reconstruction and mutual information minimization, achieving up to 3.93% higher accuracy than prior methods.