Probabilistic Embedding Of Discrete Sets As Continuous Metric Spaces

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dc.creatorBlanchard, Ph.
dc.creatorVolchenkov, D.
dc.date2008-04-28
dc.date.accessioned2026-07-07T09:35:38Z
dc.date.available2026-07-07T09:35:38Z
dc.descriptionAny symmetric affinity function $w: V\times V \to \mathbb{R}_+$ defined on a discrete set $V$ induces Euclidean space structure on $V$. In particular, an undirected graph specified by an affinity (or adjacency) matrix can be considered as a metric topological space. We have calculated the visual representations of the probabilistic locus for a chain, a polyhedron, and a finite 2-dimensional lattice.
dc.description13 pages, 7 figures, conference "Stochastic Analysis and Applications", 5-10 November 2007 Hammamet, Tunis
dc.identifierhttps://arxiv.org/abs/0804.4434
dc.identifierhttp://arxiv.org/abs/0804.4434
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/159894
dc.subjectMathematical Physics
dc.titleProbabilistic Embedding Of Discrete Sets As Continuous Metric Spaces
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