Shuffled Model of Federated Learning: Privacy, Communication and
Accuracy Trade-offs

Shuffled Model of Federated Learning: Privacy, Communication and Accuracy Trade-offs

17 August 2020

Antonious M. Girgis

Suhas Diggavi

Papers citing "Shuffled Model of Federated Learning: Privacy, Communication and Accuracy Trade-offs"

8 / 8 papers shown

Title
Stronger Privacy Amplification by Shuffling for Rényi and Approximate Differential Privacy Vitaly Feldman Audra McMillan Kunal Talwar FedML 26 47 0 09 Aug 2022
Optimal Algorithms for Mean Estimation under Local Differential Privacy Hilal Asi Vitaly Feldman Kunal Talwar 29 41 0 05 May 2022
Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message Badih Ghazi Ravi Kumar Pasin Manurangsi Rasmus Pagh Amer Sinha FedML 65 36 0 27 Sep 2021
On Large-Cohort Training for Federated Learning Zachary B. Charles Zachary Garrett Zhouyuan Huo Sergei Shmulyian Virginia Smith FedML 21 113 0 15 Jun 2021
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation Peter Kairouz Ziyu Liu Thomas Steinke FedML 27 232 0 12 Feb 2021
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