Exponential Stability of Partial Primal-Dual Gradient Dynamics with Nonsmooth Objective Functions
Zhaojian Wang, Wei Wei, Changhong Zhao, Zetian Zheng, Yunfan Zhang, Feng Liu · arXiv (Cornell University) · 2020
In this paper, we investigate the continuous time partial primal-dual gradient dynamics (P-PDGD) for solving convex optimization problems with the form $ \min\limits_{x\in X,y\inΩ}\ f({x})+h(y),\ \textit{s.t.}\ A{x}+By=C $, where $ f({x}) $ is strongly convex and smooth, but $ h(y) $ is strongly convex and non-smooth. Affine equality and set constraints are included. We prove the exponential stability of P-PDGD, and bounds on decaying rates are provided. Moreover, it is also shown that the decaying rates can be regulated by setting the stepsize.