Bohyung Han

FedLPA: Local Prior Alignment for Heterogeneous Federated Generalized Category Discovery

Local Prior Alignment (LPA) is introduced, a self-distillation mechanism that aligns batch-level predictions with empirical class prior derived from concept assignments that achieves robust generalized category discovery under severe data heterogeneity.