Titlebook: Randomized Algorithms: Approximation, Generation, and Counting; Russ Bubley Book 2001 Springer-Verlag London Limited 2001 Discrete Mathema

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鳴叫

Distinguished Dissertationshttp://image.papertrans.cn/r/image/821123.jpg

Myelin

https://doi.org/10.1007/978-1-4471-0695-1Discrete Mathematics; Erfüllbarkeitsproblem der Aussagenlogik; Markov Chain; Monte Carlo Method; Path Co

Synchronism

Mathematical Background,In this chapter we review the mathematical setting within which the research in this book is set. We also introduce much of the common notation that is used elsewhere in this book, and review some simple results that we will use in subsequent chapters.

戲服

Techniques for Sampling and Approximate Sampling,In this chapter, we review contemporary techniques for sampling from a set of combinatorial objects. We initially consider some simple methods for sampling exactly from a desired distribution, before turning to the techniques which form the basis for much of the work in this book: approximate sampling via the Markov chain method.

大吃大喝

Approximate Counting,Why do we want to count? Faced with this somewhat flippant question most people would splutter before saying that it would be in order to know how big something was. And flippant though the question is, and trivial though the answer, that really is the most salient reason.

commodity

Applications: Path Coupling,In this chapter we consider a variety of applications of the path coupling method to show rapid-mixing (or in some cases more rapid-mixing) of certain Markov chains. In each case, the associated exact counting problem is #P-complete.

過剩

詞匯記憶方法

978-1-4471-1180-1Springer-Verlag London Limited 2001

Incisor

Intermezzo, [32]. In this chapter, we slightly generalize the original path coupling argument [21, 27] by omitting a symmetry requirement. A similar and independent refinement was recently made by Dyer and Greenhill [47].