On projection mappings and the gradient projection method on hyperbolic space forms

Abstract This paper presents several new properties of the intrinsic $\kappa $-projection into $\kappa $-hyperbolically convex sets of $\kappa $-hyperbolic space forms, along with closed-form formulas for the intrinsic $\kappa $-projection into specific $\kappa $-hyperbolically convex sets. It also discusses the relationship between the intrinsic $\kappa $-projection, the Euclidean orthogonal projection and the Lorentz projection. These properties lay the groundwork for analyzing the gradient projection method and hold importance in their own right. Additionally, new properties of the gradient projection method to solve constrained optimization problems in $\kappa $-hyperbolic space forms are established, considering both constant and backtracking step sizes in the analysis. It is shown that every accumulation point of the sequence generated by the method for both step sizes is a stationary point for the given problem. Additionally, an iteration complexity bound is provided that upper bounds the number of iterations needed to achieve a suitable measure of stationarity for both step sizes. Finally, the properties of the constrained Fermat–Weber problem are explored, demonstrating that the sequence generated by the gradient projection method converges to its unique solution. Numerical experiments on solving the Fermat–Weber problem are presented, illustrating the theoretical findings and demonstrating the effectiveness of the proposed methods.

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Publication Details

Journal
IMA Journal of Numerical Analysis
Published
2025-08-14
DOI
https://doi.org/10.1093/imanum/draf097
Primary Topic
Advanced Optimization Algorithms Research
Type
article
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article

On projection mappings and the gradient projection method on hyperbolic space forms

S. Z. Németh, Jinzhen Zhu, O. P. Ferreira, Ronny Bergmann
IMA Journal of Numerical Analysis
Advanced Optimization Algorithms Research
article

On projection mappings and the gradient projection method on hyperbolic space forms

S. Z. Németh, Jinzhen Zhu, O. P. Ferreira, Ronny Bergmann
article en

Abstract

Abstract This paper presents several new properties of the intrinsic $\kappa $-projection into $\kappa $-hyperbolically convex sets of $\kappa $-hyperbolic space forms, along with closed-form formulas for the intrinsic $\kappa $-projection into specific $\kappa $-hyperbolically convex sets. It also discusses the relationship between the intrinsic $\kappa $-projection, the Euclidean orthogonal projection and the Lorentz projection. These properties lay the groundwork for analyzing the gradient projection method and hold importance in their own right. Additionally, new properties of the gradient projection method to solve constrained optimization problems in $\kappa $-hyperbolic space forms are established, considering both constant and backtracking step sizes in the analysis. It is shown that every accumulation point of the sequence generated by the method for both step sizes is a stationary point for the given problem. Additionally, an iteration complexity bound is provided that upper bounds the number of iterations needed to achieve a suitable measure of stationarity for both step sizes. Finally, the properties of the constrained Fermat–Weber problem are explored, demonstrating that the sequence generated by the gradient projection method converges to its unique solution. Numerical experiments on solving the Fermat–Weber problem are presented, illustrating the theoretical findings and demonstrating the effectiveness of the proposed methods.

IMA Journal of Numerical Analysis
Norwegian University of Science and Technology (NO), Department of Mathematical Sciences (RU), Instituto Federal de Goiás (BR), Universidade Federal de Goiás (BR), University of Birmingham (GB)
Openalex Percentile: Top 49%
Advanced Optimization Algorithms Research
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On projection mappings and the gradient projection method on hyperbolic space forms — S. Z. Németh, Jinzhen Zhu, et al. · IMA Journal of Numerical Analysis (2025) | TGRS Research Map | TGRS