Fast convergence of dynamical systems with implicit Hessian damping and Tikhonov regularization

Fuente: arXiv
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Auteurs principaux: Li, Hong-lu, He, Xin, Xiao, Yi-bin
Format: Preprint
Publié: 2025
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author Li, Hong-lu
He, Xin
Xiao, Yi-bin
author_facet Li, Hong-lu
He, Xin
Xiao, Yi-bin
contents This paper proposes novel primal-dual dynamical systems for solving linear equality constrained convex optimization. First, we introduce a primal-dual dynamical system with implicit Hessian damping, which can neutralize the transversal oscillations without requiring computation of the Hessian matrix. We establish the fast convergence properties of the proposed dynamical system under suitable conditions. Furthermore, we incorporate a Tikhonov regularization term and prove that the resulting trajectories converge strongly to the minimum norm solution. Numerical experiments are conducted to validate the theoretical findings.
format Preprint
id arxiv_https___arxiv_org_abs_2506_19545
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Fast convergence of dynamical systems with implicit Hessian damping and Tikhonov regularization
Li, Hong-lu
He, Xin
Xiao, Yi-bin
Optimization and Control
This paper proposes novel primal-dual dynamical systems for solving linear equality constrained convex optimization. First, we introduce a primal-dual dynamical system with implicit Hessian damping, which can neutralize the transversal oscillations without requiring computation of the Hessian matrix. We establish the fast convergence properties of the proposed dynamical system under suitable conditions. Furthermore, we incorporate a Tikhonov regularization term and prove that the resulting trajectories converge strongly to the minimum norm solution. Numerical experiments are conducted to validate the theoretical findings.
title Fast convergence of dynamical systems with implicit Hessian damping and Tikhonov regularization
topic Optimization and Control
url https://arxiv.org/abs/2506.19545