Efficient Federated Learning against Heterogeneous and Non-stationary
Client Unavailability

Efficient Federated Learning against Heterogeneous and Non-stationary Client Unavailability

26 September 2024

Stratis Ioannidis

Edmund Yeh

Carlee Joe-Wong

Papers citing "Efficient Federated Learning against Heterogeneous and Non-stationary Client Unavailability"

5 / 5 papers shown

Title
Heterogeneity-Aware Client Sampling: A Unified Solution for Consistent Federated Learning Shudi Weng Chao Ren Ming Xiao Mikael Skoglund FedML 5 0 0 16 May 2025
FedCanon: Non-Convex Composite Federated Learning with Efficient Proximal Operation on Heterogeneous Data Yuan Zhou Jiachen Zhong Xinli Shi G. Wen Xinghuo Yu FedML 38 0 0 16 Apr 2025
Towards Optimal Heterogeneous Client Sampling in Multi-Model Federated Learning Haoran Zhang Zejun Gong Zekai Li Marie Siew Carlee Joe-Wong Rachid El-Azouzi 31 0 0 07 Apr 2025
From Interpretation to Correction: A Decentralized Optimization Framework for Exact Convergence in Federated Learning Bicheng Ying Zhe Li Haibo Yang FedML 68 0 0 25 Mar 2025
Debiasing Federated Learning with Correlated Client Participation Zhenyu Sun Ziyang Zhang Zheng Xu Gauri Joshi Pranay Sharma Ermin Wei FedML 24 0 0 02 Oct 2024