Discrete probability theory and the theory of algorithms have become close partners over the last ten years, though the roots of this partnership go back much l

Leave nothing to chance. This cliche embodies the common belief that ran domness has no place in carefully planned methodologies, every step should be spelled o

The emphasis in this book is placed on general models (Markov chains, random fields, random graphs), universal methods (the probabilistic method, the coupling m

This title organizes computational probability methods into a systematic treatment. The book examines two categories of problems. "Algorithms for Continuous Ran

Randomization and probabilistic techniques play an important role in modern computer science, with applications ranging from combinatorial optimization and mach