A Lyapunov analysis of Korpelevich’s extragradient method with fast and flexible extensions
(2026) In Mathematical Programming- Abstract
We develop a Lyapunov-based analysis of Korpelevich’s extragradient method and show that it achieves an o(1/k) last-iterate convergence rate of the constructed Lyapunov function. This Lyapunov function simultaneously upper bounds several standard measures of optimality, which allows our analysis to sharpen existing last-iterate convergence guarantees for these measures. Moreover, the same analysis enables the design of a class of flexible extensions of the extragradient method in which extragradient steps are adaptively blended with user-specified directions via a Lyapunov-guided line-search procedure. These extensions retain global convergence under practical assumptions and can attain superlinear rates when the directions are chosen... (More)
We develop a Lyapunov-based analysis of Korpelevich’s extragradient method and show that it achieves an o(1/k) last-iterate convergence rate of the constructed Lyapunov function. This Lyapunov function simultaneously upper bounds several standard measures of optimality, which allows our analysis to sharpen existing last-iterate convergence guarantees for these measures. Moreover, the same analysis enables the design of a class of flexible extensions of the extragradient method in which extragradient steps are adaptively blended with user-specified directions via a Lyapunov-guided line-search procedure. These extensions retain global convergence under practical assumptions and can attain superlinear rates when the directions are chosen appropriately. Numerical experiments confirm the simplicity and efficiency of the proposed framework.
(Less)
- author
- Upadhyaya, Manu
LU
; Latafat, Puya
and Giselsson, Pontus
LU
- organization
- publishing date
- 2026
- type
- Contribution to journal
- publication status
- epub
- subject
- keywords
- Extragradient method, Lyapunov analysis, Monotone inclusions, Superlinear convergence
- in
- Mathematical Programming
- publisher
- Springer Nature
- external identifiers
-
- scopus:105029179059
- ISSN
- 0025-5610
- DOI
- 10.1007/s10107-025-02322-0
- language
- English
- LU publication?
- yes
- id
- a9371abc-b458-41f0-abba-9bfa055b0baa
- date added to LUP
- 2026-02-20 14:34:45
- date last changed
- 2026-02-20 14:35:57
@article{a9371abc-b458-41f0-abba-9bfa055b0baa,
abstract = {{<p>We develop a Lyapunov-based analysis of Korpelevich’s extragradient method and show that it achieves an o(1/k) last-iterate convergence rate of the constructed Lyapunov function. This Lyapunov function simultaneously upper bounds several standard measures of optimality, which allows our analysis to sharpen existing last-iterate convergence guarantees for these measures. Moreover, the same analysis enables the design of a class of flexible extensions of the extragradient method in which extragradient steps are adaptively blended with user-specified directions via a Lyapunov-guided line-search procedure. These extensions retain global convergence under practical assumptions and can attain superlinear rates when the directions are chosen appropriately. Numerical experiments confirm the simplicity and efficiency of the proposed framework.</p>}},
author = {{Upadhyaya, Manu and Latafat, Puya and Giselsson, Pontus}},
issn = {{0025-5610}},
keywords = {{Extragradient method; Lyapunov analysis; Monotone inclusions; Superlinear convergence}},
language = {{eng}},
publisher = {{Springer Nature}},
series = {{Mathematical Programming}},
title = {{A Lyapunov analysis of Korpelevich’s extragradient method with fast and flexible extensions}},
url = {{http://dx.doi.org/10.1007/s10107-025-02322-0}},
doi = {{10.1007/s10107-025-02322-0}},
year = {{2026}},
}