Biased Boltzmann samplers and generation of extended linear languages with shuffle

This paper is devoted to the construction of Boltzmann samplers according to various distributions, and uses stochastic bias on the parameter of a Boltzmann sampler, to produce a sampler with a different distribution for the size of the output. As a significant application, we produce Boltzmann samp...

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Bibliographic Details
Published in:	Discrete mathematics and theoretical computer science Vol. DMTCS Proceedings vol. AQ,...; no. Proceedings; pp. 125 - 140
Main Authors:	Darrasse, Alexis, Panagiotou, Konstantinos, Roussel, Olivier, Soria, Michele
Format:	Journal Article Conference Proceeding
Language:	English
Published:	DMTCS 01.01.2012 Discrete Mathematics and Theoretical Computer Science Discrete Mathematics & Theoretical Computer Science
Series:	DMTCS Proceedings
Subjects:	[info.info-cg] computer science [cs]/computational geometry [cs.cg] [info.info-dm] computer science [cs]/discrete mathematics [cs.dm] [info.info-ds] computer science [cs]/data structures and algorithms [cs.ds] [math.math-co] mathematics [math]/combinatorics [math.co] biased distributions boltzmann samplers combinatorial specifications Combinatorics Computational Geometry Computer Science Data Structures and Algorithms Discrete Mathematics generating functions Mathematics random sampling shuffle operator generating functions random sampling combinatorial specifications shuffle operator Boltzmann samplers biased distributions
ISSN:	1365-8050, 1462-7264, 1365-8050
Online Access:	Get full text
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