TU Darmstadt / ULB / TUprints

Quantitative analysis of a subgradient-type method for equilibrium problems

Pischke, Nicholas ; Kohlenbach, Ulrich (2024)
Quantitative analysis of a subgradient-type method for equilibrium problems.
In: Numerical Algorithms, 2022, 90 (1)
doi: 10.26083/tuprints-00023489
Article, Secondary publication, Publisher's Version

[img] Text
s11075-021-01184-9.pdf
Copyright Information: CC BY 4.0 International - Creative Commons, Attribution.

Download (2MB)
Item Type: Article
Type of entry: Secondary publication
Title: Quantitative analysis of a subgradient-type method for equilibrium problems
Language: English
Date: 24 September 2024
Place of Publication: Darmstadt
Year of primary publication: May 2022
Place of primary publication: Dordrecht
Publisher: Springer Science
Journal or Publication Title: Numerical Algorithms
Volume of the journal: 90
Issue Number: 1
DOI: 10.26083/tuprints-00023489
Corresponding Links:
Origin: Secondary publication DeepGreen
Abstract:

We use techniques originating from the subdiscipline of mathematical logic called ‘proof mining’ to provide rates of metastability and—under a metric regularity assumption—rates of convergence for a subgradient-type algorithm solving the equilibrium problem in convex optimization over fixed-point sets of firmly nonexpansive mappings. The algorithm is due to H. Iiduka and I. Yamada who in 2009 gave a noneffective proof of its convergence. This case study illustrates the applicability of the logic-based abstract quantitative analysis of general forms of Fejér monotonicity as given by the second author in previous papers.

Uncontrolled Keywords: Equilibrium problems, Firmly nonexpansive mappings, Subgradient-type method, Proof mining
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-234897
Additional Information:

Mathematics Subject Classification (2010) 47H06, 47J25, 90C33, 03F10

Classification DDC: 500 Science and mathematics > 510 Mathematics
Divisions: 04 Department of Mathematics > Logic
Date Deposited: 24 Sep 2024 11:36
Last Modified: 26 Sep 2024 07:42
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/23489
PPN: 521695899
Export:
Actions (login required)
View Item View Item