Exponential Stability of Partial Primal-Dual Gradient Dynamics with Nonsmooth Objective Functions

preprint2020arXivOpen access

Abstract

In this paper, we investigate the continuous time partial primal-dual gradient dynamics (P-PDGD) for solving convex optimization problems with the form min⁡x∈X,y∈Ω f(x)+h(y), s.t. Ax+By=C \min\limits_{x\in X,y\inΩ}\ f({x})+h(y),\ \textit{s.t.}\ A{x}+By=C , where f(x) f({x}) is strongly convex and smooth, but h(y) 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.

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