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The present application concerns a computer-implemented method for training a machine learning model in a distributed fashion, using Stochastic Gradient Descent, SGD, wherein the method is performed by a first computer in a distributed computing environmen ...
2019
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Shared objects are the means by which processes gather and exchange information about the state of a distributed system. Objects that disclose more information about the system are therefore more desirable. In this paper, we propose the schedule reconstruc ...
2017
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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 ...
ACM2017
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Shared objects are the means by which processes gather and exchange information about the state of a distributed system. Objects that disclose more information about the system—and thus provide a more centralized view—are therefore more desirable. In this ...
