Zijun Feng

FedUP: Uncertainty-Aware Personalized Federated Learning via Probabilistic Prototypes

Prototype-based federated learning enables efficient knowledge sharing by exchanging class prototypes rather than full model parameters. However, heterogeneous client data and limited local samples increase prototype estimation variance, making many client prototypes unreliable. Existing methods usu