Publication details

ACCELERATION AND GLOBAL CONVERGENCE OF A FIRST-ORDER PRIMAL-DUAL METHOD FOR NONCONVEX PROBLEMS

Authors

CLASON Christian MAZURENKO Stanislav VALKONEN Tuomo

Year of publication 2019
Type Article in Periodical
Magazine / Source SIAM JOURNAL ON OPTIMIZATION
MU Faculty or unit

Faculty of Science

Citation
web https://epubs.siam.org/doi/10.1137/18M1170194
Doi http://dx.doi.org/10.1137/18M1170194
Keywords acceleration; convergence; global; primal-dual; first order; nonconvex
Description The primal-dual hybrid gradient method, modified (PDHGM, also known as the Chambolle-Pock method), has proved very successful for convex optimization problems involving linear operators arising in image processing and inverse problems. In this paper, we analyze an extension to nonconvex problems that arise if the operator is nonlinear. Based on the idea of testing, we derive new step-length parameter conditions for the convergence in infinite-dimensional Hilbert spaces and provide acceleration rules for suitably (locally and/or partially) monotone problems. Importantly, we prove linear convergence rates as well as global convergence in certain cases. We demonstrate the efficacy of these step-length rules for PDE-constrained optimization problems.

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