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Title: Advances in Kernel Methods: Support Vector Learning by Bernhard Schölkopf, Christopher J. C. Burges, Alexander J. Smola ISBN: 0-262-19416-3 Publisher: MIT Press Pub. Date: 18 December, 1998 Format: Hardcover Volumes: 1 List Price(USD): $55.00

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Average Customer Rating: 4 (1 review)

Rating: 4
Summary: a summary of research on support vector machines
Comment: This is a collection of papers presented at a NIPS workshop held in 1997. So it provides a good entry point for access to forefronts of this rapidly developing field. Many leading researchers have contributed to this volume including V. vapnik who wrote a very succinct and readable survey. The introduction (Chapter 1) is also very useful. Though all chapters are written by leading experts in their areas and are enjoy to read. Personally I like particularly Part II on implementation in large data sets. G. Wahba provides some background on RKHS theory and a statistical perspective from GACV, for which she is mainly responsible for its popularity in statistics. I recommend this book for researchers and practitioners who may want more details and update recent developments.

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