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arXiv · 2409.18285

Primal-dual Accelerated Mirror-Descent Method for Constrained Bilinear Saddle-Point Problems

Weijian Li·Xianlin Zeng·Lacra Pavel
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Abstract

We develop a first-order accelerated algorithm for a class of constrained bilinear saddle-point problems with applications to network systems. The algorithm is a modified time-varying primal-dual version of an accelerated mirror-descent dynamics. It deals with constraints such as simplices and convex set constraints effectively, and converges with a rate of $O(1/t^2)$. Furthermore, we employ the acceleration scheme to constrained distributed optimization and bilinear zero-sum games, and obtain two variants of distributed accelerated algorithms.

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Weijian Li, Xianlin Zeng, Lacra Pavel. 2024-09-26. Primal-dual Accelerated Mirror-Descent Method for Constrained Bilinear Saddle-Point Problems. https://arxiv.org/abs/2409.18285

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