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We report on \emph{Krum}, the first \emph{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.
Olga Fink, Gaëtan Michel Frusque, Qi Li, Baorui Dai
Ali H. Sayed, Stefan Vlaski, Virginia Bordignon
Martin Louis Lucien Rémy Barry