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- Title
A semi-Bregman proximal alternating method for a class of nonconvex problems: local and global convergence analysis.
- Authors
Cohen, Eyal; Luke, D. Russell; Pinta, Titus; Sabach, Shoham; Teboulle, Marc
- Abstract
We focus on nonconvex and non-smooth block optimization problems, where the smooth coupling part of the objective does not satisfy a global/partial Lipschitz gradient continuity assumption. A general alternating minimization algorithm is proposed that combines two proximal-based steps, one classical and another with respect to the Bregman divergence. Combining different analytical techniques, we provide a complete analysis of the behavior—from global to local—of the algorithm, and show when the iterates converge globally to critical points with a locally linear rate for sufficiently regular (though not necessarily convex) objectives. Numerical experiments illustrate the theoretical findings.
- Subjects
LIPSCHITZ continuity; NONSMOOTH optimization; BEHAVIORAL assessment
- Publication
Journal of Global Optimization, 2024, Vol 89, Issue 1, p33
- ISSN
0925-5001
- Publication type
Article
- DOI
10.1007/s10898-023-01334-4