Probability and Computing

书名：Probability and ComputingRandomizationandProbabilisticTechniquesinAlgorithmsandDataAnalysis
作者：MichaelMitzenmacher/EliUpfal
译者：
ISBN：9781107154889
出版社：CambridgeUniversityPress
出版时间：2017-7-3
格式：epub/mobi/azw3/pdf
页数：484
豆瓣评分：

书籍简介：

Greatly expanded, this new edition requires only an elementary background in discrete mathematics and offers a comprehensive introduction to the role of randomization and probabilistic techniques in modern computer science. Newly added chapters and sections cover topics including normal distributions, sample complexity, VC dimension, Rademacher complexity, power laws and related distributions, cuckoo hashing, and the Lovasz Local Lemma. Material relevant to machine learning and big data analysis enables students to learn modern techniques and applications. Among the many new exercises and examples are programming-related exercises that provide students with excellent training in solving relevant problems. This book provides an indispensable teaching tool to accompany a one- or two-semester course for advanced undergraduate students in computer science and applied mathematics.

作者简介：

Review

'As randomized methods continue to grow in importance, this textbook provides a rigorous yet accessible introduction to fundamental concepts that need to be widely known. The new chapters in this second edition, about sample size and power laws, make it especially valuable for today's applications.' Donald E. Knuth, Stanford University'Of all the courses I have taught at Berkeley, my favorite is the one based on the Mitzenmacher-Upfal book Probability and Computing. Students appreciate the clarity and crispness of the arguments and the relevance of the material to the study of algorithms. The new Second Edition adds much important material on continuous random variables, entropy, randomness and information, advanced data structures and topics of current interest related to machine learning and the analysis of large data sets.' Richard M. Karp, University of California, Berkeley'The new edition is great. I'm especially excited that the authors have added sections on the normal distribution, learning theory and power laws. This is just what the doctor ordered or, more precisely, what teachers such as myself ordered!' Anna Karlin, University of Washington

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Book Description

This greatly expanded new edition, requiring only an elementary background in discrete mathematics, comprehensively covers randomization and probabilistic techniques in modern computer science. It includes new material relevant to machine learning and big data analysis, plus examples and exercises, enabling students to learn modern techniques and applications.

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书友短评：

@ Marine 经典入门教材, 概率论在CS领域的各种应用的简介. 后续推荐《the probabilistic methods》及<randomised algorithms> @ 有为 有答案的书！救我狗命！ @ 常宇 不能更赞了……虽然是上课指定教材，但作为自学材料也完全没问题，易读易懂，内容也比较新。 @ 石浥子 这学期的Textbook，内容还是比较inspiring的，但遗憾的是配图太少，有的地方理解并不直观。 @ Roy 这学期的Textbook，内容还是比较inspiring的，但遗憾的是配图太少，有的地方理解并不直观。 @ Marine 经典入门教材, 概率论在CS领域的各种应用的简介. 后续推荐《the probabilistic methods》及<randomised algorithms> @ shimmeringx 随机分析的经典。比randomized algorithm一书浅显易懂得多，而又没有丢掉核心内容。 @ 常宇 不能更赞了……虽然是上课指定教材，但作为自学材料也完全没问题，易读易懂，内容也比较新。

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