Global convergence of proximal iteratively reweighted algorithm

Tao Sun (), Hao Jiang and Lizhi Cheng
Additional contact information
Tao Sun: National University of Defense Technology
Hao Jiang: National University of Defense Technology
Lizhi Cheng: National University of Defense Technology

Journal of Global Optimization, 2017, vol. 68, issue 4, No 7, 815-826

Abstract: Abstract In this paper, we investigate the convergence of the proximal iteratively reweighted algorithm for a class of nonconvex and nonsmooth problems. Such problems actually include numerous models in the area of signal processing and machine learning research. Two extensions of the algorithm are also studied. We provide a unified scheme for these three algorithms. With the Kurdyka–Łojasiewicz property, we prove that the unified algorithm globally converges to a critical point of the objective function.

Keywords: Proximal iteratively reweighted algorithm; Kurdyka–Łojasiewicz function; Convergence analysis; Parallel splitting; Alternating updating; 90C30; 90C26; 47N10 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s10898-017-0507-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:jglopt:v:68:y:2017:i:4:d:10.1007_s10898-017-0507-z

Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/10898

DOI: 10.1007/s10898-017-0507-z

Access Statistics for this article

Journal of Global Optimization is currently edited by Sergiy Butenko

More articles in Journal of Global Optimization from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().