1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2026
pFedUL: Layer-Aware Federated Unlearning for Personalized Federated Learning
Zhuodong Liu, Xiangyu Li, Zhihao Zhang
Federated unlearning (FU) enables the removal of specific data contributions from federated learning (FL) models to comply with regulations such as the General Data Protection Regu…
cs.LG2022★ 1 cited
HFedMS: Heterogeneous Federated Learning with Memorable Data Semantics in Industrial Metaverse
Shenglai Zeng, Zonghang Li, Hongfang Yu +4
Federated Learning (FL), as a rapidly evolving privacy-preserving collaborative machine learning paradigm, is a promising approach to enable edge intelligence in the emerging Indus…