Title	Probabilistic Methods for Algorithmic Discrete Mathematics [electronic resource] / edited by Michel Habib, Colin McDiarmid, Jorge Ramirez-Alfonsin, Bruce Reed
Imprint	Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1998
Connect to	http://dx.doi.org/10.1007/978-3-662-12788-9
Descript	XVII, 325 p. online resource

The book gives an accessible account of modern pro- babilistic methods for analyzing combinatorial structures and algorithms. Each topic is approached in a didactic manner but the most recent developments are linked to the basic ma- terial. Extensive lists of references and a detailed index will make this a useful guide for graduate students and researchers. Special features included: - a simple treatment of Talagrand inequalities and their applications - an overview and many carefully worked out examples of the probabilistic analysis of combinatorial algorithms - a discussion of the "exact simulation" algorithm (in the context of Markov Chain Monte Carlo Methods) - a general method for finding asymptotically optimal or near optimal graph colouring, showing how the probabilistic method may be fine-tuned to explit the structure of the underlying graph - a succinct treatment of randomized algorithms and derandomization techniques

The Probabilistic Method -- Probabilistic Analysis of Algorithms -- An Overview of Randomized Algorithms -- Mathematical Foundations of the Markov Chain Monte Carlo Method -- Percolation and the Random Cluster Model: Combinatorial and Algorithmic Problems -- Concentration -- Branching Processes and Their Applications in the Analysis of Tree Structures and Tree Algorithms -- Author Index