A geometric condition for uniqueness of Fréchet means of persistence diagrams

IF 0.7 4区 计算机科学 Q4 MATHEMATICS Computational Geometry-Theory and Applications Pub Date : 2025-09-01 Epub Date: 2024-12-30 DOI:10.1016/j.comgeo.2024.102162
Yueqi Cao, Anthea Monod
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Abstract

The Fréchet mean is an important statistical summary and measure of centrality of data; it has been defined and studied for persistent homology captured by persistence diagrams. However, the complicated geometry of the space of persistence diagrams implies that the Fréchet mean for a given set of persistence diagrams is not necessarily unique, which prohibits theoretical guarantees for empirical means with respect to population means. In this paper, we derive a variance expression for a set of persistence diagrams exhibiting a multi-matching between the persistence points known as a grouping. Moreover, we propose a condition for groupings, which we refer to as flatness; we prove that sets of persistence diagrams that exhibit flat groupings give rise to unique Fréchet means. We derive a finite sample convergence result for general groupings, which results in convergence for Fréchet means if the groupings are flat. We then interpret flat groupings in a recently-proposed general framework of Fréchet means in Alexandrov geometry. Finally, we show that for manifold-valued data, the persistence diagrams can be truncated to construct flat groupings.
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持久性图的一个几何条件
法氏平均是一种重要的统计汇总和数据中心性度量;它已经被定义并研究了持久化图所捕获的持久化同构。然而,持久性图空间的复杂几何结构意味着给定的持久性图集合的fr平均值不一定是唯一的,这就妨碍了对总体平均值的经验平均值的理论保证。在本文中,我们推导了一组持久性图的方差表达式,这些持久性图显示了称为分组的持久性点之间的多重匹配。此外,我们提出了一个条件,我们称之为平坦性;我们证明了显示平面分组的持久性图集产生了唯一的fr切法。我们得到了一般群的有限样本收敛结果,该结果表明当群是平的时,对于frimchet means是收敛的。然后,我们在最近提出的亚历山德罗夫几何中fr均值的一般框架中解释平群。最后,我们证明了对于流形值数据,可以截断持久性图以构造平面分组。
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来源期刊
CiteScore
1.60
自引率
16.70%
发文量
43
审稿时长
>12 weeks
期刊介绍: Computational Geometry is a forum for research in theoretical and applied aspects of computational geometry. The journal publishes fundamental research in all areas of the subject, as well as disseminating information on the applications, techniques, and use of computational geometry. Computational Geometry publishes articles on the design and analysis of geometric algorithms. All aspects of computational geometry are covered, including the numerical, graph theoretical and combinatorial aspects. Also welcomed are computational geometry solutions to fundamental problems arising in computer graphics, pattern recognition, robotics, image processing, CAD-CAM, VLSI design and geographical information systems. Computational Geometry features a special section containing open problems and concise reports on implementations of computational geometry tools.
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