Statistical Learning Theory (Adaptive and Learning Systems for Signal Processing, Communications and Control Series) by Vladimir N. Vapnik

by Vladimir N. Vapnik

This book is devoted to the statistical theory of learning and generalization, that is, the problem of choosing the desired function on the basis of empirical data. The author will present the whole picture of learning and generalization theory. Learning theory has applications in many fields, such as psychology, education and computer science.

Genres: Artificial Intelligence, Science, Mathematics, Academic, Reference

Paperback

First published September 16, 1998

Reviews

[Yan Zhu · Rating 5 out of 5]

This work will become a master piece. However, it didn't get the appreciation it deserves nowadays. Yes this book is full of mathematical equations. However, if u go through the book carefully, u will notice that the author put a lot of efforts on the presentation. Given the topics and the depth covered, the book is very well organized: Big picture is frequently highlighted; deep insights r often shared around with each discussion; the proofs r crystal clean.

To ppl who comments this book as crap, the best response is given by the author himself in Page 684 the last second paragraph! (Don't be afraid, no math there:))

[Leonardo]

Vapnik es el padre de SVM. My respect

[Robert · Rating 4 out of 5]

"The Bible".

Before Deep Learning a lot more people were concerned with Statistical Learning Theory.