Yu-Can Zhou

Release the Potential of Relative Feature Consistency for Data Heterogeneous Federated Learning

Federated Learning is a promising paradigm to achieve privacy-preserving collaborative training. However, its performance degrades severely under data heterogeneity. A main obstacle is the divergent local representations induced by data heterogeneity, which will degrade the quality of the aggregated global representati...