An inertial Tseng's type proximal algorithm for nonsmooth and nonconvex optimization problems
Optimization and Control
2014-06-04 v1 Numerical Analysis
Abstract
We investigate the convergence of a forward-backward-forward proximal-type algorithm with inertial and memory effects when minimizing the sum of a nonsmooth function with a smooth one in the absence of convexity. The convergence is obtained provided an appropriate regularization of the objective satisfies the Kurdyka-\L{}ojasiewicz inequality, which is for instance fulfilled for semi-algebraic functions.
Cite
@article{arxiv.1406.0724,
title = {An inertial Tseng's type proximal algorithm for nonsmooth and nonconvex optimization problems},
author = {Radu Ioan Bot and Ernö Robert Csetnek},
journal= {arXiv preprint arXiv:1406.0724},
year = {2014}
}