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Algorithms for Random Generation and Counting: A Markov Chain Approach

✍ Scribed by A. Sinclair


Publisher
BirkhΓ€user Boston
Year
1993
Tongue
English
Leaves
79
Series
Progress in Theoretical Computer Science
Edition
1
Category
Library

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πŸ“œ SIMILAR VOLUMES


Algorithms for Random Generation and Cou
✍ Alistair Sinclair (auth.) πŸ“‚ Library πŸ“… 1993 πŸ› BirkhΓ€user Basel 🌐 English

<p>This monograph is a slightly revised version of my PhD thesis [86], comΒ­ pleted in the Department of Computer Science at the University of EdinΒ­ burgh in June 1988, with an additional chapter summarising more recent developments. Some of the material has appeared in the form of papers [50,88]. Th

Randomized Algorithms: Approximation, Ge
✍ Russ Bubley MA, PhD (auth.) πŸ“‚ Library πŸ“… 2001 πŸ› Springer-Verlag London 🌐 English

<p><B>Randomized Algorithms</B> discusses two problems of fine pedigree: counting and generation, both of which are of fundamental importance to discrete mathematics and probability. When asking questions like "How many are there?" and "What does it look like on average?" of families of combinatoria

Randomized algorithms approximation gene
✍ Russ Bubley πŸ“‚ Library πŸ“… 2000 πŸ› Springer 🌐 English

Randomized Algorithms discusses two problems of fine pedigree: counting and generation, both of which are of fundamental importance to discrete mathematics and probability. When asking questions like "How many are there?" and "What does it look like on average?" of families of combinatorial structur

Denumerable Markov chains: Generating fu
✍ Woess W. πŸ“‚ Library πŸ“… 2009 πŸ› EMS 🌐 English

Markov chains are among the basic and most important examples of random processes. This book is about time-homogeneous Markov chains that evolve with discrete time steps on a countable state space. A specific feature is the systematic use, on a relatively elementary level, of generating functions as