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arXiv:1609.03961 [math.OC]AbstractReferencesReviewsResources

Fast Algorithms for Distributed Optimization and Hypothesis Testing: A Tutorial

Alex Olshevsky

Published 2016-09-13Version 1

We consider several problems in the field of distributed optimization and hypothesis testing. We show how to obtain convergence times for these problems that scale linearly with the total number of nodes in the network by using a recent linear-time algorithm for the average consensus problem.

Comments: Tutorial paper, to appear in Proc. of CDC 2016
Categories: math.OC
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