Probabilistic Methods for Algorithmic Discrete Mathematics [electronic 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.

Bibliographic Details

Main Authors:	Habib, Michel. editor., McDiarmid, Colin. editor., Ramirez-Alfonsin, Jorge. editor., Reed, Bruce. editor., SpringerLink (Online service)
Format:	Texto biblioteca
Language:	eng
Published:	Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1998
Subjects:	Mathematics., Computers., Computer science, Probabilities., Discrete mathematics., Combinatorics., Discrete Mathematics., Computation by Abstract Devices., Symbolic and Algebraic Manipulation., Probability Theory and Stochastic Processes.,
Online Access:	http://dx.doi.org/10.1007/978-3-662-12788-9
Tags:	Add Tag No Tags, Be the first to tag this record!