Adaptive Feature Mixture for Batch-Level Personalization in Heterogeneous Federated Learning

pFedAFM proposes a novel model-heterogeneous personalized federated learning approach that achieves batch-level personalization through an adaptive feature mixture of global generalized and local personalized representations.