Si-Yi Deng

FedLEAF: Bi-directional Prototype Adaptation for Heterogeneous Federated Learning

Prototype-based knowledge sharing effectively mitigates data and model heterogeneity in federated learning (FL) by exchanging class-level semantic information. However, existing methods typically assume all local prototypes are equally reliable. Consequently, low-quality prototypes from heterogeneous models or dynamic...