BlockFLow: An Accountable and Privacy-Preserving Solution for Federated Learning

8 July 2020

Papers citing "BlockFLow: An Accountable and Privacy-Preserving Solution for Federated Learning"

5 / 5 papers shown

Title
Federated Variance-Reduced Stochastic Gradient Descent with Robustness to Byzantine Attacks Zhaoxian Wu Qing Ling Tianyi Chen G. Giannakis FedML AAML 52 182 0 29 Dec 2019
Decentralized & Collaborative AI on Blockchain Justin D. Harris Bo Waggoner SyDa 33 108 0 16 Jul 2019
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 125 1,461 0 10 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
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 264 4,620 0 18 Oct 2016