Recycled ADMM: Improve Privacy and Accuracy with Less Computation in Distributed Algorithms

7 October 2018

Papers citing "Recycled ADMM: Improve Privacy and Accuracy with Less Computation in Distributed Algorithms"

8 / 8 papers shown

Title
Topology-Dependent Privacy Bound For Decentralized Federated Learning Qiongxiu Li Wenrui Yu Changlong Ji Richard Heusdens 32 3 0 13 Dec 2023
Differentially Private Decentralized Optimization with Relay Communication Luqing Wang Luyao Guo Shaofu Yang Xinli Shi 28 0 0 21 Dec 2022
FedGiA: An Efficient Hybrid Algorithm for Federated Learning Shenglong Zhou Geoffrey Ye Li FedML 31 16 0 03 May 2022
Privacy-Preserving Distributed Processing: Metrics, Bounds, and Algorithms Qiongxiu Li Jaron Skovsted Gundersen Richard Heusdens M. G. Christensen 8 33 0 02 Sep 2020
A Critical Overview of Privacy-Preserving Approaches for Collaborative Forecasting Carla Gonccalves R. Bessa Pierre Pinson 22 29 0 20 Apr 2020
Differentially Private ADMM for Distributed Medical Machine Learning Jiahao Ding Xiaoqi Qin Wenjun Xu Yanmin Gong Zhu Han Miao Pan FedML 32 20 0 07 Jan 2019
DP-ADMM: ADMM-based Distributed Learning with Differential Privacy Zonghao Huang Rui Hu Yuanxiong Guo Eric Chan-Tin Yanmin Gong FedML 11 193 0 30 Aug 2018
Distributed Event Localization via Alternating Direction Method of Multipliers Chunlei Zhang Yongqiang Wang 31 27 0 13 Jul 2016