ResearchTrend.AI
Recycled ADMM: Improving the Privacy and Accuracy of Distributed Algorithms

Recycled ADMM: Improving the Privacy and Accuracy of Distributed Algorithms

Xueru Zhang
Mohammad Mahdi Khalili
M. Liu
ArXiv (abs)PDFHTML

Papers citing "Recycled ADMM: Improving the Privacy and Accuracy of Distributed Algorithms"

4 / 4 papers shown
Title
Federated Coordinate Descent for Privacy-Preserving Multiparty Linear Regression
Federated Coordinate Descent for Privacy-Preserving Multiparty Linear Regression
Xinlin Leng
Chenxu Li
Weifeng Xu
Yuyan Sun
Hongtao Wang
FedML
49
1
0
16 Sep 2022
Quantization enabled Privacy Protection in Decentralized Stochastic Optimization
Quantization enabled Privacy Protection in Decentralized Stochastic Optimization
Yongqiang Wang
Tamer Basar
43
47
0
07 Aug 2022
Tailoring Gradient Methods for Differentially-Private Distributed Optimization
Tailoring Gradient Methods for Differentially-Private Distributed Optimization
Yongqiang Wang
A. Nedić
121
75
0
02 Feb 2022
Local SGD with Periodic Averaging: Tighter Analysis and Adaptive Synchronization
Local SGD with Periodic Averaging: Tighter Analysis and Adaptive Synchronization
Farzin Haddadpour
Mohammad Mahdi Kamani
M. Mahdavi
V. Cadambe
FedML
87
201
0
30 Oct 2019

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.