arXiv:1406.0724 Abstract | arXiv Analytics

arXiv:1406.0724 [math.OC]Abstract References Reviews Resources

An inertial Tseng's type proximal algorithm for nonsmooth and nonconvex optimization problems

Published 2014-06-03Version 1

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.

Categories: math.OC, math.NA

Subjects: 90C26, 90C30, 65K10

Keywords: inertial tsengs type proximal algorithm, nonconvex optimization problems, semi-algebraic functions, appropriate regularization, forward-backward-forward proximal-type algorithm

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