The Nature Of Statistical Learning Theory 2nd Ed Www Usamarketplace Info rar (0387987800)

Review

From the reviews of the second edition:

ZENTRALBLATT MATH

"...written in a concise style. It must be recommended to scientists of statistics, mathematics, physics, and computer science."

SHORT BOOK REVIEWS

"This interesting book helps a reader to understand the interconnections between various streams in the empirical modeling realm and may be recommended to any reader who feels lost in modern terminology, such as artificial intelligence, neural networks, machine learning etcetera."

"The book by Vapnik focuses on how to estimate a function of parameters from empirical data . The book is concisely written and is intended to be useful to statisticians, computer scientists, mathematicians, and physicists. This book is very well written at a very high level of abstract thinking and comprehension. The references are up-to-date." (Ramalingam Shanmugam, Journal of Statistical Computation and Simulation, Vol. 75 (2), February, 2005)

"The aim of the book is to introduce a wide range of readers to the fundamental ideas of statistical learning theory. Each chapter is supplemented by Reasoning and Comments which describe the relations between classical research in mathematical statistics and research in learning theory. The book is well suited to promote the ideas of statistical learning theory and can be warmly recommended to all who are interested in computer learning problems." (S. Vogel, Metrika, June, 2002)

Product Description

The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. These include: * the setting of learning problems based on the model of minimizing the risk functional from empirical data * a comprehensive analysis of the empirical risk minimization principle including necessary and sufficient conditions for its consistency * non-asymptotic bounds for the risk achieved using the empirical risk minimization principle * principles for controlling the generalization ability of learning machines using small sample sizes based on these bounds * the Support Vector methods that control the generalization ability when estimating function using small sample size. The second edition of the book contains three new chapters devoted to further development of the learning theory and SVM techniques. These include: * the theory of direct method of learning based on solving multidimensional integral equations for density, conditional probability, and conditional density estimation * a new inductive principle of learning. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists. Vladimir N. Vapnik is Technology Leader AT&T Labs-Research and Professor of London University. He is one of the founders of statistical learning theory, and the author of seven books published in English, Russian, German, and Chinese.

See all Editorial Reviews

Product Details

* Hardcover: 332 pages

* Publisher: Springer; 2nd ed. edition (November 19, 1999)

* Language: English

* ISBN-10: 0387987800

* ISBN-13: 978-0387987804

Buy Book at Lowest Price on Amazon

Code: Please say thanks if you download to keep this topic alive!

Server	Status
Download Links
Direct Download Link 1	Alive
Direct Download Link 2	Alive
Check Download Links	Alive
Download Link (Download Link 1)	Alive
Buy This Book at Best Price >>

	Mathematics The nature of statistical learning theory. Second Edition
	Mathematics Statistical Learning Theory
	Science/Engineering Vladimir N. Vapnik - Statistical Learning Theory Vladimir N. Vapnik, "Statistical Learning Theory"John Wiley & Sons \| ISBN : 0471030031 \| Year - 1998 \| DjVu \| 5.8 MB \| 732 PagesA comprehensive look at learning and generalization theory. The statistical theory of learning and generalizatio ...
	Science/Engineering Information Theory and Statistical Learning Information Theory and Statistical Learning Publisher: Springer \| Pages: 407 \| 2008-11-10 \| ISBN 0387848150 \| PDF \| 10 MBInformation Theory and Statistical Learning presents theoretical and practical results about information theo ...
	Science/Engineering Vladimir N. Vapnik, "The Nature of Statistical Learning Theory" (2nd edition) (Repost) Vladimir N. Vapnik, "The Nature of Statistical Learning Theory" (2nd edition)Springer \| ISBN 0387987800 \| 1999 Year \| DjVu \| 2,23 Mb \| 314 PagesThe aim of this book is to discuss the fundamental ideas which lie behind the statistical theory ...
	Study Information Theory and Statistical Learning (ReUp) Frank Emmert-Streib, Matthias Dehmer, "Information Theory and Statistical Learning" Springer 2008 \| ISBN-10: 0387848150 \| 389 Pages \| PDF \| 10,6 MB Information Theory and Statistical Learning presents theoretical and practical results abou ...

Share this page with your friends now!
Text link
Forum (BBCode)
Website (HTML)

Book123

Categories

Share With Friends

Archive by Date

Search Tag

Newest

Useful Links

The Nature of Statistical Learning Theory

Related Articles

DISCLAIMER:

Comments (0) All