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On the Rate of Convergence of Iterative Methods for Nonexpansive Mappings in CAT(0) Spaces and Hyperbolic Optimization

2025/10/29 by Foglia, Katherine Rossella, Colao, Vittorio
#FOS: Mathematics #Functional Analysis (math.FA) #Optimization and Control (math.OC)

paper · doi:10.48550/arxiv.2510.25363

Abstract

The Krasnosel'ski\uı Mann and Halpern iterations are classical schemes for approximating fixed points of nonexpansive mappings in Banach spaces, and have been widely studied in more general frameworks such as CAT(κ) and, more generally, geodesic spaces. Convergence results and convergence rate estimates in these nonlinear settings are already well established. The contribution of this paper is to extend to complete CAT(0) spaces the proof techniques originally developed in the linear setting of Banach and Hilbert spaces, thereby recovering the same asymptotic regularity bounds and to introduce a novel optimizer for Hyperbolic Deep learning based on Halpern Iteration similarly to HalpernSGD \citefoglia2024halpernsgd,colao2025optimizer in Euclidean setting.

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