Title: A note on the accelerated proximal gradient method for nonconvex optimization.
Authors: HUIJUAN WANG; HONG-KUN XU
Abstract: We improve a recent accelerated proximal gradient (APG) method in [Li, Q., Zhou, Y., Liang, Y. and Varshney, P. K., Convergence analysis of proximal gradient with momentum for nonconvex optimization, in Proceedings of the 34th International Conference on Machine Learning, Sydney, Australia, PMLR 70, 2017] for nonconvex optimization by allowing variable stepsizes. We prove the convergence of the APG method for a composite nonconvex optimization problem under the assumption that the composite objective function satisfies the Kurdyka-Łojasiewicz property.
Subjects: MATHEMATICAL optimization; MATHEMATICAL functions; SET theory; MATHEMATICAL mappings; MATHEMATICAL proofs
Publication: Carpathian Journal of Mathematics, 2018, Vol 34, Issue 3, p449
ISSN: 1584-2851
Publication type: Academic Journal
DOI: 10.37193/cjm.2018.03.22

A note on the accelerated proximal gradient method for nonconvex optimization.

HUIJUAN WANG; HONG-KUN XU