6 citations · 8 across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 2 cited
Fast Heterogeneous Federated Learning with Hybrid Client Selection
Guangyuan Shen, Dehong Gao, Duanxiao Song +5
Client selection schemes are widely adopted to handle the communication-efficient problems in recent studies of Federated Learning (FL). However, the large variance of the model up…
cs.LG2022★ 6 cited
Variance-Reduced Heterogeneous Federated Learning via Stratified Client Selection
Guangyuan Shen, Dehong Gao, Libin Yang +4
Client selection strategies are widely adopted to handle the communication-efficient problem in recent studies of Federated Learning (FL). However, due to the large variance of the…