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Auteurs principaux: Xie, Yixin, Liu, Jin-Peng, Sun, Cong, Yuan, Ya-Xiang
Format: Preprint
Publié: 2026
Sujets:
Accès en ligne:https://arxiv.org/abs/2602.13141
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author Xie, Yixin
Liu, Jin-Peng
Sun, Cong
Yuan, Ya-Xiang
author_facet Xie, Yixin
Liu, Jin-Peng
Sun, Cong
Yuan, Ya-Xiang
contents A new stepsize for gradient method is proposed. Combining it with the exact line search stepsizes, the gradient method achieves the optimal solution in 5 steps for 3 dimensional quadratic function minimization problem. The new stepsize is plugged in the cyclic stepsize update strategy, and a new gradient method is proposed. By applying the quadratic interpolation for Cauchy approximation, the proposed gradient method is extended to solve general unconstrained problem. With the improved GLL line search, the global convergence of the proposed method is proved. Furthermore, its sublinear convergence rate for convex problems and R-linear convergence rate for problems with quadratic functional growth property are analyzed. Numerical results show that our proposed algorithm enjoys good performances in terms of computational cost, and line search requires very few trial stepsizes.
format Preprint
id arxiv_https___arxiv_org_abs_2602_13141
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle New gradient methods with 3 dimensional quadratic termination
Xie, Yixin
Liu, Jin-Peng
Sun, Cong
Yuan, Ya-Xiang
Optimization and Control
65K05, 90C30
A new stepsize for gradient method is proposed. Combining it with the exact line search stepsizes, the gradient method achieves the optimal solution in 5 steps for 3 dimensional quadratic function minimization problem. The new stepsize is plugged in the cyclic stepsize update strategy, and a new gradient method is proposed. By applying the quadratic interpolation for Cauchy approximation, the proposed gradient method is extended to solve general unconstrained problem. With the improved GLL line search, the global convergence of the proposed method is proved. Furthermore, its sublinear convergence rate for convex problems and R-linear convergence rate for problems with quadratic functional growth property are analyzed. Numerical results show that our proposed algorithm enjoys good performances in terms of computational cost, and line search requires very few trial stepsizes.
title New gradient methods with 3 dimensional quadratic termination
topic Optimization and Control
65K05, 90C30
url https://arxiv.org/abs/2602.13141