Random Descent Steps in a Probability Maximization Scheme

Edit Csizmás (), Rajmund Drenyovszki (), Tamás Szántai () and Csaba I. Fábián ()
Additional contact information
Edit Csizmás: John von Neumann University
Rajmund Drenyovszki: John von Neumann University
Tamás Szántai: Budapest University of Technology and Economics
Csaba I. Fábián: John von Neumann University

Journal of Optimization Theory and Applications, 2025, vol. 205, issue 1, No 13, 26 pages

Abstract: Abstract Gradient computation of multivariate distribution functions calls for considerable effort. Hence coordinate descent and derivative-free approaches are attractive. This paper deals with constrained convex problems. We perform random descent steps in an approximation scheme that is an inexact cutting-plane method from a dual viewpoint. We prove that the scheme converges and present a computational study comparing different descent methods applied in the approximation scheme.

Keywords: Stochastic programming; Probability maximization; Approximation schemes; Coordinate-descent methods; Cutting-plane methods (search for similar items in EconPapers)
Date: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10957-025-02619-2 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:joptap:v:205:y:2025:i:1:d:10.1007_s10957-025-02619-2

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2

DOI: 10.1007/s10957-025-02619-2

Access Statistics for this article

Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull

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