Fast Heterogeneous Federated Learning with Hybrid Client Selection

no code implementations • 10 Aug 2022 • Guangyuan Shen, Dehong Gao, Duanxiao Song, Libin Yang, Xukai Zhou, Shirui Pan, Wei Lou, Fang Zhou

We present a novel clustering-based client selection scheme to accelerate the FL convergence by variance reduction.

Clustering Federated Learning

Variance-Reduced Heterogeneous Federated Learning via Stratified Client Selection

no code implementations • 15 Jan 2022 • Guangyuan Shen, Dehong Gao, Libin Yang, Fang Zhou, Duanxiao Song, Wei Lou, Shirui Pan

However, due to the large variance of the selected subset's update, prior selection approaches with a limited sampling ratio cannot perform well on convergence and accuracy in heterogeneous FL.

Federated Learning