Random posets, lattices, and lattices terms
Jaroslav Ježek, Václav Slavík (2000)
Mathematica Bohemica
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Algorithms for generating random posets, random lattices and random lattice terms are given.
Jaroslav Ježek, Václav Slavík (2000)
Mathematica Bohemica
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Algorithms for generating random posets, random lattices and random lattice terms are given.
Le Borgne, Yvan, Marckert, Jean-François (2007)
The Electronic Journal of Combinatorics [electronic only]
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Diaconis, Persi, Holmes Susan (2002)
Electronic Journal of Probability [electronic only]
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Kuba, M., Panholzer, A., Prodinger, H. (2009)
The Electronic Journal of Combinatorics [electronic only]
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Alexander S. Kechris, Miodrag Sokić (2012)
Fundamenta Mathematicae
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A method is developed for proving non-amenability of certain automorphism groups of countable structures and is used to show that the automorphism groups of the random poset and random distributive lattice are not amenable. The universal minimal flow of the automorphism group of the random distributive lattice is computed as a canonical space of linear orderings but it is also shown that the class of finite distributive lattices does not admit hereditary order expansions with the Amalgamation...
Fill, James Allen, Huber, Mark L. (2010)
Electronic Journal of Probability [electronic only]
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Grimmett, Geoffrey, Janson, Svante (2009)
The Electronic Journal of Combinatorics [electronic only]
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Hans C. Andersen, Persi Diaconis (2007)
Journal de la société française de statistique
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We present a generalization of hit and run algorithms for Markov chain Monte Carlo problems that is ‘equivalent’ to data augmentation and auxiliary variables. These algorithms contain the Gibbs sampler and Swendsen-Wang block spin dynamics as special cases. The unification allows theorems, examples, and heuristics developed in one domain to illuminate parallel domains.
Vojtěch Franěk (2008)
Commentationes Mathematicae Universitatis Carolinae
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Many low-discrepancy sets are suitable for quasi-Monte Carlo integration. Skriganov showed that the intersections of suitable lattices with the unit cube have low discrepancy. We introduce an algorithm based on linear programming which scales any given lattice appropriately and computes its intersection with the unit cube. We compare the quality of numerical integration using these low-discrepancy lattice sets with approximations using other known (quasi-)Monte Carlo methods. The comparison...
Tohru Ogawa, Yukihisa Nakajima (2000)
Visual Mathematics
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