A note on the convergence of nonconvex line search
Numerical Analysis
2016-03-23 v1 Numerical Analysis
Abstract
In this note, we consider the line search for a class of abstract nonconvex algorithm which have been deeply studied in the Kurdyka-Lojasiewicz theory. We provide a weak convergence result of the line search in general. When the objective function satisfies the Kurdyka-Lojasiewicz property and some certain assumption, a global convergence result can be derived. An application is presented for the L0-regularized least square minimization in the end of the paper.
Keywords
Cite
@article{arxiv.1603.06912,
title = {A note on the convergence of nonconvex line search},
author = {Tao Sun and Lizhi Chenga and Hao Jiang},
journal= {arXiv preprint arXiv:1603.06912},
year = {2016}
}