Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms

6 June 2018

Xueru Zhang

Mohammad Mahdi Khalili

M. Liu

FedML

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Papers citing "Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms"

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Title
Privacy Amplification by Iteration for ADMM with (Strongly) Convex Objective Functions T.-H. Hubert Chan Hao Xie Mengshi Zhao 53 1 0 14 Dec 2023
Topology-Dependent Privacy Bound For Decentralized Federated Learning Qiongxiu Li Wenrui Yu Changlong Ji Richard Heusdens 37 3 0 13 Dec 2023
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning Edwige Cyffers A. Bellet D. Basu FedML 39 5 0 24 Feb 2023
Differentially Private Decentralized Optimization with Relay Communication Luqing Wang Luyao Guo Shaofu Yang Xinli Shi 38 0 0 21 Dec 2022
Differentially Private ADMM-Based Distributed Discrete Optimal Transport for Resource Allocation Jason Hughes Juntao Chen OT 26 1 0 30 Nov 2022
FedGiA: An Efficient Hybrid Algorithm for Federated Learning Shenglong Zhou Geoffrey Ye Li FedML 38 16 0 03 May 2022
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey Shangwei Guo Xu Zhang Feiyu Yang Tianwei Zhang Yan Gan Tao Xiang Yang Liu FedML 36 9 0 19 Dec 2021
Communication-Efficient ADMM-based Federated Learning Shenglong Zhou Geoffrey Ye Li FedML 40 22 0 28 Oct 2021
Fair Sequential Selection Using Supervised Learning Models Mohammad Mahdi Khalili Xueru Zhang Mahed Abroshan FaML 36 20 0 26 Oct 2021
Encrypted Distributed Lasso for Sparse Data Predictive Control A. Alexandru Anastasios Tsiamis George J. Pappas 17 10 0 23 Apr 2021
Privacy-preserving Decentralized Aggregation for Federated Learning Beomyeol Jeon S. Ferdous Muntasir Raihan Rahman A. Walid FedML 33 52 0 13 Dec 2020
Privacy Amplification by Decentralization Edwige Cyffers A. Bellet FedML 54 39 0 09 Dec 2020
Privacy-Preserving Distributed Processing: Metrics, Bounds, and Algorithms Qiongxiu Li Jaron Skovsted Gundersen Richard Heusdens M. G. Christensen 19 33 0 02 Sep 2020
Topology-aware Differential Privacy for Decentralized Image Classification Shangwei Guo Tianwei Zhang Guowen Xu Hanzhou Yu Tao Xiang Yang Liu 27 18 0 14 Jun 2020
Privacy-preserving Incremental ADMM for Decentralized Consensus Optimization Yu Ye Hao Chen Ming Xiao Mikael Skoglund H. Vincent Poor 31 28 0 24 Mar 2020
Recycled ADMM: Improving the Privacy and Accuracy of Distributed Algorithms Xueru Zhang Mohammad Mahdi Khalili M. Liu FedML 15 23 0 08 Oct 2019
DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression Hanlin Tang Xiangru Lian Chen Yu Tong Zhang Ji Liu 11 217 0 15 May 2019
Differentially Private ADMM for Distributed Medical Machine Learning Jiahao Ding Xiaoqi Qin Wenjun Xu Yanmin Gong Zhu Han Miao Pan FedML 39 20 0 07 Jan 2019
Recycled ADMM: Improve Privacy and Accuracy with Less Computation in Distributed Algorithms Xueru Zhang Mohammad Mahdi Khalili M. Liu 39 30 0 07 Oct 2018
DP-ADMM: ADMM-based Distributed Learning with Differential Privacy Zonghao Huang Rui Hu Yuanxiong Guo Eric Chan-Tin Yanmin Gong FedML 22 194 0 30 Aug 2018