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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.
Ali H. Sayed, Stefan Vlaski, Virginia Bordignon
Olga Fink, Gaëtan Michel Frusque, Qi Li, Baorui Dai
Martin Louis Lucien Rémy Barry