2017
Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent
NeurIPS 2017poster
We study the resilience to Byzantine failures of distributed implementations of Stochastic Gradient Descent (SGD). So far, distributed machine learning frameworks have largely ignored the possibility of failures, especially arbitrary (i.e., Byzantine) ones. Causes of failures include software bugs…