A Class of Randomized Primal-Dual Algorithms for Distributed Optimization

24 Jun 2014Jean-Christophe PesquetAudrey Repetti

Based on a preconditioned version of the randomized block-coordinate forward-backward algorithm recently proposed in [Combettes,Pesquet,2014], several variants of block-coordinate primal-dual algorithms are designed in order to solve a wide array of monotone inclusion problems. These methods rely on a sweep of blocks of variables which are activated at each iteration according to a random rule, and they allow stochastic errors in the evaluation of the involved operators... (read more)

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