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A perfect sampling algorithm of random walks with forbidden arcs

Stéphane Durand 1 Bruno Gaujal 1 Florence Perronnin 1 Jean-Marc Vincent 1
1 MESCAL - Middleware efficiently scalable
Inria Grenoble - Rhône-Alpes, LIG [2007-2015] - Laboratoire d'Informatique de Grenoble [2007-2015]
Abstract : In this paper we show how to construct an algorithm to sample the stationary distribution of a random walk over ${1,...,N}^d$ with forbidden arcs. This algorithm combines the rejection method and coupling from the past of a set of trajectories of the Markov chain that generalizes the classical sandwich approach. We also provide a complexity analysis of this approach in several cases showing a coupling time in $O(N^2 d log d )$ when no arc is forbidden and an experimental study of its performance.
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Contributor : Florence Perronnin <>
Submitted on : Tuesday, September 30, 2014 - 11:43:53 AM
Last modification on : Friday, July 17, 2020 - 11:10:24 AM

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Stéphane Durand, Bruno Gaujal, Florence Perronnin, Jean-Marc Vincent. A perfect sampling algorithm of random walks with forbidden arcs. QEST 2014 - 11th International Conference on Quantitative Evaluation of Systems, Sep 2014, Florence, Italy. pp.178-193, ⟨10.1007/978-3-319-10696-0_15⟩. ⟨hal-01069975⟩



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