Sch¨olkopf and Smola: Learning with Kernels 2001/09/24 10:30
Learning with Kernels
Adaptive Computation and Machine Learning
Thomas Dietterich, Editor
Christopher Bishop, David Heckerman, Michael Jordan, and Michael Kearns, As-
sociate Editors
Bioinformatics: The Machine Learning Approach, Pierre Baldi and Søren Brunak
Reinforcement Learning: An Introduction, Richard S. Sutton and Andrew G. Barto
Graphical Models for Machine Learning and Digital Communication, Brendan J. Frey
Learning in Graphical Models, Michael I. Jordan
Causation, Prediction, and Search, second edition, Peter Spirtes, Clark Glymour, and
Richard Scheines
Principles of Data Mining, David Hand, Heikki Mannila, and Padhraic Smyth
Bioinformatics: The Machine Learning Approach, second edition, Pierre Baldi and
Søren Brunak
Learning Kernel Classifiers: Theory and Algorithms, Ralf Herbrich
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and
Beyond, Bernhard Sch¨olkopf and Alexander J. Smola
Sch¨olkopf and Smola: Learning with Kernels 2001/09/24 10:30
Learning with Kernels
Support Vector Machines, Regularization, Optimization, and Beyond
Bernhard Sch¨olkopf
Alexander J. Smola
The MIT Press
Cambridge, Massachusetts
London, England
c
2002 Massachusetts Institute of Technology
All rights reserved. No part of this book may be reproduced in any form by any electronic or
mechanical means (including photocopying, recording, or information storage and retrieval) without
permission in writing from the publisher.
Typeset by the authors using L
A
T
E
X2
Printed and bound in the United States of America
Library of Congress Cataloging-in-Publication Data
Learning with Kernels — Support Vector Machines,
Regularization, Optimization and Beyond / by Bernhard Sch¨olkopf,
Alexander J. Smola.
p. cm.
Includes bibliographical references and index.
ISBN 0-262-19475-9 (alk. paper)
1. Machine learning. 2. Algorithms. 3. Kernel functions
I. Sch¨olkopf, Bernhard. II. Smola, Alexander J.
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