Information Theory, Inference, and Learning Algorithms

阿瑟豆腐干红酒

Information theory and inference, often taught separately, are here united in one entertaining textbook. These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook introduces theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks. The final part of the book describes the state of the art in error-correcting codes, including low-density parity-check codes, turbo codes, and digital fountain codes -- the twenty-first century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, David MacKay's groundbreaking book is ideal for self-learning and for undergraduate or graduate courses. Interludes on crosswords, evolution, and sex provide entertainment along the way. In sum, this is a textbook on information, communication, and coding for a new generation of students, and an unparalleled entry point into these subjects for professionals in areas as diverse as computational biology, financial engineering, and machine learning.

MargaretS

听说过，没看过

sigpp

bucuobucuo

liuwei_0613

MacKay的经典名著，有关信息论、机器学习和LDPC的内容却又独到之处，有翻译的中文版，谢谢楼主共享！

姬岐阳

回复 1# 阿瑟豆腐干红酒


   感谢楼主谢谢

姬岐阳

回复 1# 阿瑟豆腐干红酒


   是不是差两卷啊

江洋

thanks

qinqinghit

回复 4# liuwei_0613


   中文版在哪里，可否分享一下，谢谢。