DiPSeN: Differentially Private Self-normalizing Neural Networks For Adversarial Robustness in Federated Learning

8 January 2021

Papers citing "DiPSeN: Differentially Private Self-normalizing Neural Networks For Adversarial Robustness in Federated Learning"

5 / 5 papers shown

Title
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 194 345 0 15 Dec 2021
On the Security & Privacy in Federated Learning Gorka Abad S. Picek Víctor Julio Ramírez-Durán A. Urbieta 42 11 0 10 Dec 2021
Gradient Masking and the Underestimated Robustness Threats of Differential Privacy in Deep Learning Franziska Boenisch Philip Sperl Konstantin Böttinger AAML 11 13 0 17 May 2021
IBM Federated Learning: an Enterprise Framework White Paper V0.1 Heiko Ludwig Nathalie Baracaldo Gegi Thomas Yi Zhou Ali Anwar ... Sean Laguna Mikhail Yurochkin Mayank Agarwal Ebube Chuba Annie Abay FedML 131 157 0 22 Jul 2020
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 261 3,109 0 04 Nov 2016