An Accurate, Scalable and Verifiable Protocol for Federated Differentially Private Averaging

12 June 2020

Papers citing "An Accurate, Scalable and Verifiable Protocol for Federated Differentially Private Averaging"

5 / 5 papers shown

Title
Towards Trustworthy Federated Learning with Untrusted Participants Youssef Allouah R. Guerraoui John Stephan FedML 53 0 0 03 May 2025
Differentially Private Empirical Cumulative Distribution Functions Antoine Barczewski Amal Mawass Jan Ramon FedML 52 0 0 10 Feb 2025
Communication-Efficient Triangle Counting under Local Differential Privacy Jacob Imola Takao Murakami Kamalika Chaudhuri 32 31 0 13 Oct 2021
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 182 1,032 0 29 Nov 2018
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 144 420 0 29 Nov 2018