Bixiao Zeng

FedES: Federated Early-Stopping for Hindering Memorizing Heterogeneous Label Noise

Federated learning (FL) facilitates collaborative model training across distributed clients while maintaining privacy. Federated noisy label learning (FNLL) is more of a challenge for data inaccessibility and noise heterogeneity. Existing works primarily assume clients are either noisy or clean, whi…