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Sampling matchings in parallel

Authors: Díaz Cort, Josep; Serna Iglesias, María José; Spirakis, Paul George;

Sampling matchings in parallel

Abstract

We present a parallel algorithm to sample matchings from an almost uniform distribution on the set of matchings of all sizes in a graph. The technique used is based on the definition of a genetic system that converges to the uniform distribution. The system evolves according to a non-linear equation. Little is known about the convergence of these systems. We can define a non-linear system which converges to a stationary distribution under quite natural conditions. We prove convergence for the system corresponding to the almost uniform sampling of matchings in a graph (up to know the only known convergence for non-linear systems for matchings was matchings on a tree). We give empirical evidence that the system converges fast.

Country
Spain
Keywords

Parallel algorithms, Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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