[PDF.38qi] An Introduction to Computational Learning Theory (MIT Press)

An Introduction to Computational Learning Theory (MIT Press)

[PDF.vh78] An Introduction to Computational Learning Theory (MIT Press)

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 | #387477 in Books |  1994-08-15 | Original language:English | PDF # 1 |  9.25 x.65 x7.10l,1.11 | File type: PDF | 221 pages

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||14 of 15 people found the following review helpful.| It turns out that complexity theorists have something valuable to say...|By Shiva Kaul|...about machine learning since learning algorithms are, in fact, algorithms. At a high level, computational learning theory answers the same sort of questions as statistical learning theory ("What kind of guarantees can I make about my learning procedure? In what situations is learning pos|About the Author|Michael J. Kearns is Professor of Computer and Information Science at the University of Pennsylvania.

Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics.Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the common methods underlying efficient learning alg...

You easily download any file type for your device.An Introduction to Computational Learning Theory (MIT Press)   |  Michael J. Kearns, Umesh Vazirani.Not only was the story interesting, engaging and relatable, it also teaches lessons.

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