Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks

14 October 2019

Papers citing "Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks"

7 / 7 papers shown

Title
On the Optimal Batch Size for Byzantine-Robust Distributed Learning Yi-Rui Yang Chang-Wei Shi Wu-Jun Li FedML AAML 27 0 0 23 May 2023
FedREP: A Byzantine-Robust, Communication-Efficient and Privacy-Preserving Framework for Federated Learning Yi-Rui Yang Kun Wang Wulu Li FedML 42 3 0 09 Mar 2023
FedCut: A Spectral Analysis Framework for Reliable Detection of Byzantine Colluders Hanlin Gu Lixin Fan Xingxing Tang Qiang Yang AAML FedML 22 1 0 24 Nov 2022
Maximizing Communication Efficiency for Large-scale Training via 0/1 Adam Yucheng Lu Conglong Li Minjia Zhang Christopher De Sa Yuxiong He OffRL AI4CE 24 20 0 12 Feb 2022
SignSGD: Fault-Tolerance to Blind and Byzantine Adversaries J. Akoun S. Meyer AAML FedML 22 1 0 04 Feb 2022
What Do We Mean by Generalization in Federated Learning? Honglin Yuan Warren Morningstar Lin Ning K. Singhal OOD FedML 41 71 0 27 Oct 2021
Buffered Asynchronous SGD for Byzantine Learning Yi-Rui Yang Wu-Jun Li FedML 29 5 0 02 Mar 2020