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

1. Mathematics
2. Computers
3. Computer science -- Mathematics
4. Probabilities
5. Discrete mathematics
6. Combinatorics
7. Mathematics
8. Discrete Mathematics
9. Combinatorics
10. Computation by Abstract Devices
11. Symbolic and Algebraic Manipulation
12. Probability Theory and Stochastic Processes