Probabilistic Methods for Algorithmic Discrete Mathematics

M. Habib, C. McDiarmid, Jorge L. Ramirez Alfonsin, B. Reed

324 pages, parution le 01/01/1998

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Résumé

The book gives an accessible account of modern probabilistic methods for analyzing combinatorial structures and algorithms. It will be an useful guide for graduate students and researchers.

Special features included:

a simple treatment of Talagrand's 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 exploit the structure of the underlying graph;
a succinct treatment of randomized algorithms and derandomization techniques

Contents

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
Subject Index

L'auteur - Jorge L. Ramirez Alfonsin

Jorge L. Ramírez Alfonsín, Maître de Conférences, Université Pierre et Marie Curie, Paris 6.

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	M. Habib, C. McDiarmid, Jorge L. Ramirez Alfonsin, B. Reed
Parution	01/01/1998
Nb. de pages	324
Format	16 x 24
Couverture	Relié
Poids	616g
Intérieur	Noir et Blanc
EAN13	9783540646228

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Probabilistic Methods for Algorithmic Discrete Mathematics

Résumé

L'auteur - Jorge L. Ramirez Alfonsin

Autres livres de Jorge L. Ramirez Alfonsin

Caractéristiques techniques

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