book announcement: Schlkopf

[Jud Wolfskill]

MIT has recently published another book I thought Connectionist readers 
might be interested in. For more information, please visit 
http://mitpress.mit.edu/0262194759/  Thank you!

Best,
Jud

Learning with Kernels
Support Vector Machines, Regularization, Optimization, and Beyond
Bernhard Schlkopf and Alexander J. Smola

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.
8 x 10, 632 pp., 138 illus., cloth, ISBN 0-262-19475-9
Adaptive Computation and Machine Learning series




Jud Wolfskill
Associate Publicist
MIT Press
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wolfskil at mit.edu