Probabilistic Methods for Algorithmic Discrete Mathematics (eBook, PDF)

Redaktion: Habib, Michel; Reed, Bruce; Ramirez-Alfonsin, Jorge; McDiarmid, Colin

• Format: PDF

Produktbeschreibung

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

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 325
• Erscheinungstermin: 14. März 2013
• Englisch
• ISBN-13: 9783662127889
• Artikelnr.: 53387883

Inhaltsangabe

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.