Mini-Batch Stochastic Krasnosel'ski\uı-Mann Algorithm for Nonexpansive Fixed Point Problems

Fuente: arXiv
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1. Verfasser: Iiduka, Hideaki
Format: Preprint
Veröffentlicht: 2026
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_version_ 1866913015781130240
author Iiduka, Hideaki
author_facet Iiduka, Hideaki
contents The Krasnosel'ski\uı-Mann algorithm is a well-known method for finding fixed points of a nonexpansive mapping with strong theoretical guarantees. However, there are practical large-scale problems to which this algorithm cannot be applied. Here, to resolve the issue caused by the computational difficulty of the mapping, we define a computable mini-batch stochastic mapping, which is a unbiased estimator of the nonexpansive mapping, and implement it in the Krasnosel'ski\uı-Mann algorithm. We show that the algorithm with increasing batch sizes converges almost surely to a fixed point of the nonexpansive mapping. We also perform a convergence rate analysis on the algorithm.
format Preprint
id arxiv_https___arxiv_org_abs_2604_06909
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Mini-Batch Stochastic Krasnosel'ski\uı-Mann Algorithm for Nonexpansive Fixed Point Problems
Iiduka, Hideaki
Optimization and Control
47J26, 65K05, 90C15
The Krasnosel'ski\uı-Mann algorithm is a well-known method for finding fixed points of a nonexpansive mapping with strong theoretical guarantees. However, there are practical large-scale problems to which this algorithm cannot be applied. Here, to resolve the issue caused by the computational difficulty of the mapping, we define a computable mini-batch stochastic mapping, which is a unbiased estimator of the nonexpansive mapping, and implement it in the Krasnosel'ski\uı-Mann algorithm. We show that the algorithm with increasing batch sizes converges almost surely to a fixed point of the nonexpansive mapping. We also perform a convergence rate analysis on the algorithm.
title Mini-Batch Stochastic Krasnosel'ski\uı-Mann Algorithm for Nonexpansive Fixed Point Problems
topic Optimization and Control
47J26, 65K05, 90C15
url https://arxiv.org/abs/2604.06909