New operator designs for Halpern iterations with explicit rates under Hölder error bounds

Fuente: arXiv
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Auteurs principaux: Barros, Pablo, Guigues, Vincent, Behling, Roger, Santos, Luiz-Rafael
Format: Preprint
Publié: 2026
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author Barros, Pablo
Guigues, Vincent
Behling, Roger
Santos, Luiz-Rafael
author_facet Barros, Pablo
Guigues, Vincent
Behling, Roger
Santos, Luiz-Rafael
contents We investigate the asymptotic behavior of Halpern-type iterations applied to quasi-nonexpansive operators arising in best approximation problems over the intersection of finitely many closed convex sets in $\mathbb{R}^n$. Assuming a local decrease condition for the underlying operator and standard requirements on the stepsizes $(α_k) \subset (0,1)$, we first prove strong convergence of the Halpern sequence $x_{k+1} = α_k x_0 + (1-α_k) T x_k$ to the best approximation point $x^\star$ in the intersection set, that is, the metric projection of $x_0$ onto that set. Under the additional assumption that the intersection satisfies a Hölder-type error bound with exponent $γ\in (0,1]$, we then derive explicit convergence rates for both feasibility and norm error: the distance from $x_k$ to the intersection set decays like $\mathcal O(α_k^{γ/(2-γ)})$, while the norm error $\|x_k - x^\star\|$ decays like $\mathcal O(α_k^{γ/(4-2γ)})$. These results apply to most projection-type operators used in convex feasibility problems (including MAP, CRM/SCCRM, Cimmino and 3PM/A3PM) and extend classical convergence analyses of the Halpern-type iterations by providing explicit, geometry-dependent rates governed by Hölder-type error bounds. Our numerical experiments show that Halpern-type iterations combined with most of these projection-type operators are quicker than Dykstra's algorithm to find the projection of a point in an intersection of ellipsoids or in an intersection of polyhedrons.
format Preprint
id arxiv_https___arxiv_org_abs_2601_14451
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle New operator designs for Halpern iterations with explicit rates under Hölder error bounds
Barros, Pablo
Guigues, Vincent
Behling, Roger
Santos, Luiz-Rafael
Optimization and Control
47H09, 47H10, 47J25, 65K10, 90C25
We investigate the asymptotic behavior of Halpern-type iterations applied to quasi-nonexpansive operators arising in best approximation problems over the intersection of finitely many closed convex sets in $\mathbb{R}^n$. Assuming a local decrease condition for the underlying operator and standard requirements on the stepsizes $(α_k) \subset (0,1)$, we first prove strong convergence of the Halpern sequence $x_{k+1} = α_k x_0 + (1-α_k) T x_k$ to the best approximation point $x^\star$ in the intersection set, that is, the metric projection of $x_0$ onto that set. Under the additional assumption that the intersection satisfies a Hölder-type error bound with exponent $γ\in (0,1]$, we then derive explicit convergence rates for both feasibility and norm error: the distance from $x_k$ to the intersection set decays like $\mathcal O(α_k^{γ/(2-γ)})$, while the norm error $\|x_k - x^\star\|$ decays like $\mathcal O(α_k^{γ/(4-2γ)})$. These results apply to most projection-type operators used in convex feasibility problems (including MAP, CRM/SCCRM, Cimmino and 3PM/A3PM) and extend classical convergence analyses of the Halpern-type iterations by providing explicit, geometry-dependent rates governed by Hölder-type error bounds. Our numerical experiments show that Halpern-type iterations combined with most of these projection-type operators are quicker than Dykstra's algorithm to find the projection of a point in an intersection of ellipsoids or in an intersection of polyhedrons.
title New operator designs for Halpern iterations with explicit rates under Hölder error bounds
topic Optimization and Control
47H09, 47H10, 47J25, 65K10, 90C25
url https://arxiv.org/abs/2601.14451