FedAdaVR: Adaptive Variance Reduction for Robust Federated Learning under Limited Client Participation
arXiv:2601.22204v2 Announce Type: replace
Abstract: Federated learning (FL) encounters substantial challenges due to heterogeneity, leading to gradient noise, client drift, and partial client participation errors, the last of which is the most pervasi…