具體描述
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.
用戶評價
概率部分基本上是從頭講起的 沒學過概率也能看懂 感動 算法分析講的好
評分 評分##很難，全部是數學理論，推導。我覺得這本數應該算數學書多一些。
評分 評分 評分##大三時zhao yunlei課的教材。書很好，隨機算法很驚艷，可惜數學渣在課程後期沒怎麼學懂
評分 評分##配閤 randomized algorithms 來看，裏麵有些相同的內容
評分相關圖書
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