most citedFedCanon: Non-Convex Composite Federated Learning with Efficient Proximal Operation on Heterogeneous Data

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2025

Decentralized Nonconvex Composite Federated Learning with Gradient Tracking and Momentum

Yuan Zhou, Xinli Shi, Xuelong Li +3

Decentralized Federated Learning (DFL) enables collaborative model training without relying on a central server. When local objectives are nonconvex and coupled with nonsmooth weak…

cs.LG2025★ 1 cited

FedCanon: Non-Convex Composite Federated Learning with Efficient Proximal Operation on Heterogeneous Data

Yuan Zhou, Jiachen Zhong, Xinli Shi +2

Composite federated learning offers a general framework for solving machine learning problems with additional regularization terms. However, existing methods often face significant…