Xingwei Huang

FedRNC: Addressing Spatio-Temporal Label Misalignment in Federated Noisy Class-Incremental Learning

Federated class-incremental learning (FCIL) aims to incrementally learn new classes across decentralized clients under non-IID data distributions. However, the pervasive challenge of label noise in FCIL has been completely overlooked. In this work, we introduce federated noisy class-incremental lear