Dropout against Deep Leakage from Gradients

v1v2 (latest)

Dropout against Deep Leakage from Gradients

25 August 2021

ArXiv (abs)PDF HTML

Papers citing "Dropout against Deep Leakage from Gradients"

4 / 4 papers shown

Title
FEDLAD: Federated Evaluation of Deep Leakage Attacks and Defenses Isaac Baglin Xiatian Zhu Simon Hadfield FedML 88 1 0 05 Nov 2024
iDLG: Improved Deep Leakage from Gradients Bo Zhao Konda Reddy Mopuri Hakan Bilen FedML 81 643 0 08 Jan 2020
Towards Federated Learning at Scale: System Design Keith Bonawitz Hubert Eichner W. Grieskamp Dzmitry Huba A. Ingerman ... H. B. McMahan Timon Van Overveldt David Petrou Daniel Ramage Jason Roselander FedML 126 2,675 0 04 Feb 2019
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems Martín Abadi Ashish Agarwal P. Barham E. Brevdo Zhiwen Chen ... Pete Warden Martin Wattenberg Martin Wicke Yuan Yu Xiaoqiang Zheng 289 11,150 0 14 Mar 2016