An Inertial Tseng’s Type Proximal Algorithm for Nonsmooth and Nonconvex Optimization Problems

Radu Ioan Boţ () and Ernö Robert Csetnek ()
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Radu Ioan Boţ: University of Vienna
Ernö Robert Csetnek: University of Vienna

Journal of Optimization Theory and Applications, 2016, vol. 171, issue 2, No 15, 600-616

Abstract: 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–Łojasiewicz inequality, which is for instance fulfilled for semi-algebraic functions.

Keywords: Nonsmooth optimization; Limiting subdifferential; Kurdyka–Łojasiewicz inequality; Bregman distance; Inertial proximal algorithm; Tseng’s type proximal algorithm; 90C26; 90C30; 65K10 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10957-015-0730-z

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