@inproceedings{0cfa5aa1a2994e628248cf86c2ec78d6,
title = "Brief announcement: Byzantine-tolerant machine learning",
abstract = "We report on Krum, the first provably Byzantine-tolerant aggregation rule for distributed Stochastic Gradient Descent (SGD). Krum guarantees the convergence of SGD even in a distributed setting where (asymptotically) up to half of the workers can be malicious adversaries trying to attack the learning system.",
keywords = "Adversarial machine learning, Distributed stochastic gradient descent",
author = "Peva Blanchard and \{El Mhamdi\}, \{El Mahdi\} and Rachid Guerraoui and Julien Stainer",
note = "Publisher Copyright: {\textcopyright} 2017 Association for Computing Machinery.; 36th ACM Symposium on Principles of Distributed Computing, PODC 2017 ; Conference date: 25-07-2017 Through 27-07-2017",
year = "2017",
month = jul,
day = "26",
doi = "10.1145/3087801.3087861",
language = "English",
series = "Proceedings of the Annual ACM Symposium on Principles of Distributed Computing",
publisher = "Association for Computing Machinery",
pages = "455--458",
booktitle = "PODC 2017 - Proceedings of the ACM Symposium on Principles of Distributed Computing",
}