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.
CITATION STYLE
Habib, M., McDiarmid, C., Ramirez-Alfonsin, J., & Reed, B. (1998). Probabilistic Methods for Algorithmic Discrete Mathematics. (M. Habib, C. McDiarmid, J. Ramirez-Alfonsin, & B. Reed, Eds.), Media (Vol. 16, p. 323). Springer Berlin Heidelberg. Retrieved from http://link.springer.com/10.1007/978-3-662-12788-9 http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:Algorithms+and+Combinatorics+24#9%5Cnhttp://books.google.com/books?id=Vx7FJy5JlcEC&pgis=1
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