具体描述
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.
用户评价
##如果有人想知道学一点初等概率论之后可以干什么，推荐读这本书
##很难，全部是数学理论，推导。我觉得这本数应该算数学书多一些。
##之前因为封面好看tag了这个 = = 然后我现在真的在学这门课…… 什么，你说你结课了就妄想自己真的读完这本书了？（
##大三时zhao yunlei课的教材。书很好，随机算法很惊艳，可惜数学渣在课程后期没怎么学懂
##大三时zhao yunlei课的教材。书很好，随机算法很惊艳，可惜数学渣在课程后期没怎么学懂
##大三时zhao yunlei课的教材。书很好，随机算法很惊艳，可惜数学渣在课程后期没怎么学懂
##之前因为封面好看tag了这个 = = 然后我现在真的在学这门课…… 什么，你说你结课了就妄想自己真的读完这本书了？（
##如果有人想知道学一点初等概率论之后可以干什么，推荐读这本书
##配合 randomized algorithms 来看，里面有些相同的内容