An Accelerated Double-Proximal Gradient Algorithm for DC Programming

Gaoxi Li (), Ying Yi and Yingquan Huang ()
Additional contact information
Gaoxi Li: School of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing 400067, P. R. China
Ying Yi: School of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing 400067, P. R. China
Yingquan Huang: Chongqing Key Laboratory of Social Economy and Applied Statistics, Chongqing 400067, P. R. China

Asia-Pacific Journal of Operational Research (APJOR), 2024, vol. 41, issue 03, 1-21

Abstract: The double-proximal gradient algorithm (DPGA) is a new variant of the classical difference-of-convex algorithm (DCA) for solving difference-of-convex (DC) optimization problems. In this paper, we propose an accelerated version of the double-proximal gradient algorithm for DC programming, in which the objective function consists of three convex modules (only one module is smooth). We establish convergence of the sequence generated by our algorithm if the objective function satisfies the Kurdyka–Šojasiewicz (KŠ) property and show that its convergence rate is not weaker than DPGA. Compared with DPGA, the numerical experiments on an image processing model show that the number of iterations of ADPGA is reduced by 43.57% and the running time is reduced by 43.47% on average.

Keywords: Difference-of-convex problems; double-proximal gradient algorithm; convergence analysis (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0217595923500288
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:apjorx:v:41:y:2024:i:03:n:s0217595923500288

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0217595923500288

Access Statistics for this article

Asia-Pacific Journal of Operational Research (APJOR) is currently edited by Gongyun Zhao

More articles in Asia-Pacific Journal of Operational Research (APJOR) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().