Renyi Differential Privacy of the Subsampled Shuffle Model in
Distributed Learning

Renyi Differential Privacy of the Subsampled Shuffle Model in Distributed Learning

19 July 2021

Antonious M. Girgis

Suhas Diggavi

Papers citing "Renyi Differential Privacy of the Subsampled Shuffle Model in Distributed Learning"

7 / 7 papers shown

Title
Learning from End User Data with Shuffled Differential Privacy over Kernel Densities Tal Wagner FedML 53 0 0 21 Feb 2025
Privacy Amplification via Shuffling: Unified, Simplified, and Tightened Shaowei Wang FedML 26 9 0 11 Apr 2023
Differentially Private Federated Learning on Heterogeneous Data Maxence Noble A. Bellet Aymeric Dieuleveut FedML 11 102 0 17 Nov 2021
Tempered Sigmoid Activations for Deep Learning with Differential Privacy Nicolas Papernot Abhradeep Thakurta Shuang Song Steve Chien Ulfar Erlingsson AAML 144 178 0 28 Jul 2020
Improved Summation from Shuffling Borja Balle James Bell Adria Gascon Kobbi Nissim FedML 48 22 0 24 Sep 2019
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 141 420 0 29 Nov 2018
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 101 570 0 08 Dec 2012