A Speed Restart Scheme for a Dynamics with Hessian-Driven Damping
Juan José Maulén () and
Juan Peypouquet ()
Additional contact information
Juan José Maulén: University of Groningen
Juan Peypouquet: University of Groningen
Journal of Optimization Theory and Applications, 2023, vol. 199, issue 2, No 15, 855 pages
Abstract:
Abstract In this paper, we analyze a speed restarting scheme for the inertial dynamics with Hessian-driven damping, introduced by Attouch et al. (J Differ Equ 261(10):5734–5783, 2016). We establish a linear convergence rate for the function values along the restarted trajectories. Numerical experiments suggest that the Hessian-driven damping and the restarting scheme together improve the performance of the dynamics and corresponding iterative algorithms in practice.
Keywords: Convex optimization; Hessian-driven damping; First-order methods; Restarting; Differential equations; 37N40; 90C25; 65K10 (primary); 34A12 (secondary) (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s10957-023-02290-5 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:199:y:2023:i:2:d:10.1007_s10957-023-02290-5
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2
DOI: 10.1007/s10957-023-02290-5
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 ().