A Class of Randomized Primal-Dual Algorithms for Distributed Optimization

@inproceedings{Pesquet2014ACO,
  title={A Class of Randomized Primal-Dual Algorithms for Distributed Optimization},
  author={Jean-Christophe Pesquet and Audrey Repetti},
  year={2014}
}
Based on a preconditioned version of the randomized block-coordinate forward-backward algorithm recently proposed in [23], 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. Then, this framework is employed to derive… CONTINUE READING
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