num_pages: 370
description: Assuming only an elementary background in discrete mathematics, this textbook is an excellent introduction to the probabilistic techniques and paradigms used in the development of probabilistic algorithms and analyses. It includes random sampling, expectations, Markov's and Chevyshev's inequalities, Chernoff bounds, balls and bins models, the probabilistic method, Markov chains, MCMC, martingales, entropy, and other topics. The book is designed to accompany a one- or two-semester course for graduate students in computer science and applied mathematics.
language: English
title: Probability and Computing: Randomized Algorithms and Probabilistic Analysis
titlecomplete: Probability and Computing: Randomized Algorithms and Probabilistic Analysis
genres: Science, Reference, Computer Science, Algorithms, Mathematics, Programming, Research, Academic, Textbooks, Nonfiction
ratings_count: 85
publisher: Cambridge University Press