FedDR -- Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization

5 March 2021

Papers citing "FedDR -- Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization"

8 / 8 papers shown

Title
Randomized Block-Coordinate Optimistic Gradient Algorithms for Root-Finding Problems Quoc Tran-Dinh Yang Luo 89 6 0 28 Jan 2025
A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs Yan Sun Li Shen Dacheng Tao FedML 25 0 0 27 Sep 2024
Distributed Event-Based Learning via ADMM Güner Dilsad Er Sebastian Trimpe Michael Muehlebach FedML 34 2 0 17 May 2024
Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape Yan Sun Li Shen Shi-Yong Chen Liang Ding Dacheng Tao FedML 27 33 0 19 May 2023
DualFL: A Duality-based Federated Learning Algorithm with Communication Acceleration in the General Convex Regime Jongho Park Jinchao Xu FedML 47 1 0 17 May 2023
FedSysID: A Federated Approach to Sample-Efficient System Identification Han Wang Leonardo F. Toso James Anderson FedML 24 17 0 25 Nov 2022
Clustered Federated Learning based on Nonconvex Pairwise Fusion Xue Yu Ziyi Liu Wu Wang Yifan Sun FedML 32 7 0 08 Nov 2022
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization Xiaoxiao Li Meirui Jiang Xiaofei Zhang Michael Kamp Qi Dou OOD FedML 168 786 0 15 Feb 2021