The Support Vector Book is now distributed and available (see http://www.support-vector.net for details). AN INTRODUCTION TO SUPPORT VECTOR MACHINES (and other kernel-based learning methods) N. Cristianini and J. Shawe-Taylor Cambridge University Press, 2000 ISBN: 0 521 78019 5 http://www.support-vector.net Contents - Overview 1 The Learning Methodology 2 Linear Learning Machines 3 Kernel-Induced Feature Spaces 4 Generalisation Theory 5 Optimisation Theory 6 Support Vector Machines 7 Implementation Techniques 8 Applications of Support Vector Machines Pseudocode for the SMO Algorithm Background Mathematics References Index Description This book is the first comprehensive introduction to Support Vector Machines (SVMs), a new generation learning system based on recent advances in statistical learning theory. The book also introduces Bayesian analysis of learning and relates SVMs to Gaussian Processes and other kernel based learning methods. SVMs deliver state-of-the-art performance in real-world applications such as text categorisation, hand-written character recognition, image classification, biosequences analysis, etc. Their first introduction in the early 1990s lead to a recent explosion of applications and deepening theoretical analysis, that has now established Support Vector Machines along with neural networks as one of the standard tools for machine learning and data mining. Students will find the book both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and application of these techniques. The concepts are introduced gradually in accessible and self-contained stages, though in each stage the presentation is rigorous and thorough. Pointers to relevant literature and web sites containing software ensure that it forms an ideal starting point for further study. These are also available on-line through an associated web site www.support- vector.net, which will be kept updated with pointers to new literature, applications, and on-line software. Sent via Deja.com http://www.deja.com/ Before you buy. =========================================================================== This list is open to everyone. Occasionally, less thoughtful people send inappropriate messages. Please DO NOT COMPLAIN TO THE POSTMASTER about these messages because the postmaster has no way of controlling them, and excessive complaints will result in termination of the list. For information about this list, including information about the problem of inappropriate messages and information about how to unsubscribe, please see the web page at http://jse.stat.ncsu.edu/ ===========================================================================
