Privacy is What We Care About: Experimental Investigation of Federated
Learning on Edge Devices

Privacy is What We Care About: Experimental Investigation of Federated Learning on Edge Devices

11 November 2019

Thomas Brunschwiler

ArXiv (abs)PDF HTML

Papers citing "Privacy is What We Care About: Experimental Investigation of Federated Learning on Edge Devices"

7 / 7 papers shown

Title
Federated Machine Learning: Concept and Applications Qiang Yang Yang Liu Tianjian Chen Yongxin Tong FedML 85 2,332 0 13 Feb 2019
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 158 1,424 0 03 Dec 2018
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 260 1,719 0 14 Apr 2018
Differentially Private Federated Learning: A Client Level Perspective Robin C. Geyer T. Klein Moin Nabi FedML 140 1,300 0 20 Dec 2017
Federated Multi-Task Learning Virginia Smith Chao-Kai Chiang Maziar Sanjabi Ameet Talwalkar FedML 162 1,818 0 30 May 2017
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 220 6,172 0 01 Jul 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 412 17,615 0 17 Feb 2016