The Privacy Power of Correlated Noise in Decentralized Learning

2 May 2024

Papers citing "The Privacy Power of Correlated Noise in Decentralized Learning"

8 / 8 papers shown

Title
Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging Edwige Cyffers Mathieu Even A. Bellet Laurent Massoulié FedML 74 25 0 10 Jun 2022
A Unified Theory of Decentralized SGD with Changing Topology and Local Updates Anastasia Koloskova Nicolas Loizou Sadra Boreiri Martin Jaggi Sebastian U. Stich FedML 78 505 0 23 Mar 2020
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 172 426 0 29 Nov 2018
Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron Sharan Vaswani Francis R. Bach Mark Schmidt 75 298 0 16 Oct 2018
DP-ADMM: ADMM-based Distributed Learning with Differential Privacy Zonghao Huang Rui Hu Yuanxiong Guo Eric Chan-Tin Yanmin Gong FedML 49 195 0 30 Aug 2018
Subsampled Rényi Differential Privacy and Analytical Moments Accountant Yu Wang Borja Balle S. Kasiviswanathan 71 398 0 31 Jul 2018
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 138 1,471 0 10 May 2018
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 375 17,399 0 17 Feb 2016