Differentially-Private "Draw and Discard" Machine Learning

11 July 2018

Papers citing "Differentially-Private "Draw and Discard" Machine Learning"

4 / 4 papers shown

Title
Dordis: Efficient Federated Learning with Dropout-Resilient Differential Privacy Zhifeng Jiang Wei Wang Ruichuan Chen 43 6 0 26 Sep 2022
Differentially Private Bayesian Inference for Generalized Linear Models Tejas D. Kulkarni Joonas Jälkö A. Koskela Samuel Kaski Antti Honkela 35 31 0 01 Nov 2020
Privacy-Preserving Boosting in the Local Setting Sen Wang J.Morris Chang FedML 15 3 0 06 Feb 2020
LEAF: A Benchmark for Federated Settings S. Caldas Sai Meher Karthik Duddu Peter Wu Tian Li Jakub Konecný H. B. McMahan Virginia Smith Ameet Talwalkar FedML 56 1,393 0 03 Dec 2018