Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond

Hardcover (Print)
Used and New from Other Sellers
Used and New from Other Sellers
from $60.81
Usually ships in 1-2 business days
(Save 30%)
Other sellers (Hardcover)
  • All (12) from $60.81   
  • New (8) from $60.81   
  • Used (4) from $60.81   

Overview

In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs -- -kernels--for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics.Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.

The MIT Press

Read More Show Less

What People Are Saying

From the Publisher

"Interesting and original. Learning with Kernels will make a fine textbook on this subject."--Grace Wahba, Bascom Professor of Statistics, University of Wisconsin Madison

The MIT Press

"This splendid book fills the need for a comprehensive treatment of kernel methods and support vector machines. It collects results, theorems, and discussions from disparate sources into one very accessible exposition. I am particularly impressed that the authors have included problem sets at the end of each chapter; such problems are not easy to construct, but add significantly to the value of the book for the student audience."--Chris J. C. Burges, Microsoft
Research

The MIT Press

Read More Show Less

Product Details

Meet the Author

Bernhard Schölkopf is Professor and Director at the Max Planck Institute for
Biological Cybernetics in Tübingen, Germany. He is coauthor of Learning with Kernels (2002) and is a coeditor of Advances in Kernel
Methods: Support Vector Learning
(1998), Advances in Large-Margin
Classifiers
(2000), and Kernel Methods in Computational
Biology
(2004), all published by the MIT Press.

Alexander J. Smola is Senior Principal Researcher and Machine Learning Program
Leader at National ICT Australia/Australian National University, Canberra.

Read More Show Less

Table of Contents

Series Foreword
Preface
1 An Tutorial Introduction 1
I Concepts and Tools 23
2 Kernels 25
3 Risk and Loss Functions 61
4 Regularization 87
5 Elements of Statistical Learning Theory 125
6 Optimization 149
II Support Vector Machines 187
7 Pattern Recognition 189
8 Single-Class Problems: Qantile Estimation and Novelty Detection 227
9 Regression Estimation 251
10 Implementation 279
11 Incorporating Invariances 333
12 Learning Theory Revisited 359
III Kernel Methods 405
13 Designing Kernels 407
14 Kernel Feature Extraction 427
15 Kernel Fisher Discriminant 457
16 Bayesian Kernel Methods 469
17 Regularized Principal Manifolds 517
18 Pre-Images and Reduced Set Methods 543
A: Addenda 569
B Mathematical Prerequisites 575
References 591
Index 617
Notation and Symbols 625
Read More Show Less

Customer Reviews

Be the first to write a review
( 0 )
Rating Distribution

5 Star

(0)

4 Star

(0)

3 Star

(0)

2 Star

(0)

1 Star

(0)

Your Rating:

Your Name: Create a Pen Name or

Barnes & Noble.com Review Rules

Our reader reviews allow you to share your comments on titles you liked, or didn't, with others. By submitting an online review, you are representing to Barnes & Noble.com that all information contained in your review is original and accurate in all respects, and that the submission of such content by you and the posting of such content by Barnes & Noble.com does not and will not violate the rights of any third party. Please follow the rules below to help ensure that your review can be posted.

Reviews by Our Customers Under the Age of 13

We highly value and respect everyone's opinion concerning the titles we offer. However, we cannot allow persons under the age of 13 to have accounts at BN.com or to post customer reviews. Please see our Terms of Use for more details.

What to exclude from your review:

Please do not write about reviews, commentary, or information posted on the product page. If you see any errors in the information on the product page, please send us an email.

Reviews should not contain any of the following:

  • - HTML tags, profanity, obscenities, vulgarities, or comments that defame anyone
  • - Time-sensitive information such as tour dates, signings, lectures, etc.
  • - Single-word reviews. Other people will read your review to discover why you liked or didn't like the title. Be descriptive.
  • - Comments focusing on the author or that may ruin the ending for others
  • - Phone numbers, addresses, URLs
  • - Pricing and availability information or alternative ordering information
  • - Advertisements or commercial solicitation

Reminder:

  • - By submitting a review, you grant to Barnes & Noble.com and its sublicensees the royalty-free, perpetual, irrevocable right and license to use the review in accordance with the Barnes & Noble.com Terms of Use.
  • - Barnes & Noble.com reserves the right not to post any review -- particularly those that do not follow the terms and conditions of these Rules. Barnes & Noble.com also reserves the right to remove any review at any time without notice.
  • - See Terms of Use for other conditions and disclaimers.
Search for Products You'd Like to Recommend

Recommend other products that relate to your review. Just search for them below and share!

Create a Pen Name

Your Pen Name is your unique identity on BN.com. It will appear on the reviews you write and other website activities. Your Pen Name cannot be edited, changed or deleted once submitted.

 
Your Pen Name can be any combination of alphanumeric characters (plus - and _), and must be at least two characters long.

Continue Anonymously

    If you find inappropriate content, please report it to Barnes & Noble
    Why is this product inappropriate?
    Comments (optional)