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arXiv · 2108.12136

Distributed Mirror Descent Algorithm with Bregman Damping for Nonsmooth Constrained Optimization

Guanpu Chen·Weijian Li·Gehui Xu·Yiguang Hong
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Abstract

To solve distributed optimization efficiently with various constraints and nonsmooth functions, we propose a distributed mirror descent algorithm with embedded Bregman damping, as a generalization of conventional distributed projection-based algorithms. In fact, our continuous-time algorithm well inherits good capabilities of mirror descent approaches to rapidly compute explicit solutions to the problems with some specific constraint structures. Moreover, we rigorously prove the convergence of our algorithm, along with the boundedness of the trajectory and the accuracy of the solution.

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Guanpu Chen, Weijian Li, Gehui Xu, Yiguang Hong. 2021-08-27. Distributed Mirror Descent Algorithm with Bregman Damping for Nonsmooth Constrained Optimization. https://arxiv.org/abs/2108.12136

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