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

Radu Ioan Bot(radu.bot***at***univie.ac.at)
Ernö Robert Csetnek(ernoe.robert.csetnek***at***univie.ac.at)

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.

Keywords: nonsmooth optimization, limiting subdifferential, Kurdyka-\L{}ojasiewicz inequality, Bregman distance, inertial proximal algorithm, Tseng's type proximal algorithm

Category 1: Convex and Nonsmooth Optimization (Nonsmooth Optimization )

Citation:

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Entry Submitted: 06/03/2014
Entry Accepted: 06/03/2014
Entry Last Modified: 06/03/2014

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