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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Veröffentlicht in:	Discrete mathematics and theoretical computer science Jg. DMTCS Proceedings vol. AQ,...; H. Proceedings; S. 125 - 140
Hauptverfasser:	Darrasse, Alexis, Panagiotou, Konstantinos, Roussel, Olivier, Soria, Michele
Format:	Journal Article Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	DMTCS 01.01.2012 Discrete Mathematics and Theoretical Computer Science Discrete Mathematics & Theoretical Computer Science
Schriftenreihe:	DMTCS Proceedings
Schlagworte:	[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-Zugang:	Volltext
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