MYSTIKO : : Cloud-Mediated, Private, Federated Gradient Descent

1 December 2020

Papers citing "MYSTIKO : : Cloud-Mediated, Private, Federated Gradient Descent"

7 / 7 papers shown

Title
HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning Runhua Xu Nathalie Baracaldo Yi Zhou Ali Anwar Heiko Ludwig FedML 35 288 0 12 Dec 2019
Deep Leakage from Gradients Ligeng Zhu Zhijian Liu Song Han FedML 56 2,185 0 21 Jun 2019
A Hybrid Approach to Privacy-Preserving Federated Learning Stacey Truex Nathalie Baracaldo Ali Anwar Thomas Steinke Heiko Ludwig Rui Zhang Yi Zhou FedML 44 889 0 07 Dec 2018
cpSGD: Communication-efficient and differentially-private distributed SGD Naman Agarwal A. Suresh Felix X. Yu Sanjiv Kumar H. B. McMahan FedML 109 490 0 27 May 2018
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 200 4,075 0 18 Oct 2016
An overview of gradient descent optimization algorithms Sebastian Ruder ODL 164 6,170 0 15 Sep 2016
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 152 6,049 0 01 Jul 2016