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Autores principales: He, Songnian, Xu, Hong-Kun, Dong, Qiao-Li, Mei, Na
Formato: Preprint
Publicado: 2025
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Acceso en línea:https://arxiv.org/abs/2505.10807
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author He, Songnian
Xu, Hong-Kun
Dong, Qiao-Li
Mei, Na
author_facet He, Songnian
Xu, Hong-Kun
Dong, Qiao-Li
Mei, Na
contents We propose an adaptive way to choose the anchoring parameters for the Halpern iteration to find a fixed point of a nonexpansive mapping in a real Hilbert space. We prove strong convergence of this adaptive Halpern iteration and obtain the rate of asymptotic regularity at least O(1/k), where k is the number of iterations. Numerical experiments are also provided to show advantages and outperformance of our adaptive Halpern algorithm over the standard Halpern algorithm.
format Preprint
id arxiv_https___arxiv_org_abs_2505_10807
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Convergence analysis of the Halpern iteration with adaptive anchoring parameters
He, Songnian
Xu, Hong-Kun
Dong, Qiao-Li
Mei, Na
Optimization and Control
We propose an adaptive way to choose the anchoring parameters for the Halpern iteration to find a fixed point of a nonexpansive mapping in a real Hilbert space. We prove strong convergence of this adaptive Halpern iteration and obtain the rate of asymptotic regularity at least O(1/k), where k is the number of iterations. Numerical experiments are also provided to show advantages and outperformance of our adaptive Halpern algorithm over the standard Halpern algorithm.
title Convergence analysis of the Halpern iteration with adaptive anchoring parameters
topic Optimization and Control
url https://arxiv.org/abs/2505.10807