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| | Description | The Support Vector Machine is a powerful new learning algorithm for solving a variety of learning and function estimation problems, such as pattern recognition, regression estimation, and operator inversion. The impetus for this collection was a workshop on Support Vector Machines held at the 1997 NIPS conference. The contributors, both university researchers and engineers developing applications for the corporate world, form a Who's Who of this exciting new area.
Contributors: Peter Bartlett, Kristin P. Bennett, Christopher J. C. Burges, Nello Cristianini, Alex Gammerman, Federico Girosi, Simon Haykin, Thorsten Joachims, Linda Kaufman, Jens Kohlmorgen, Ulrich Kreßel, Davide Mattera, Klaus-Robert Müller, Manfred Opper, Edgar E. Osuna, John C. Platt, Gunnar Rätsch, Bernhard Schölkopf, John Shawe-Taylor, Alexander J. Smola, Mark O. Stitson, Vladimir Vapnik, Volodya Vovk, Grace Wahba, Chris Watkins, Jason Weston, Robert C. Williamson. | |
| | Product Details | | Hardcover: | 386 pages | | Publisher: | The MIT Press | | Publication Date: | December 18, 1998 | | Language: | English | | ISBN: | 0262194163 | | Package Length: | 10.27 inches | | Package Width: | 8.31 inches | | Package Height: | 1.31 inches | | Package Weight: | 2.73 pounds | | Average Customer Rating: |  based on 1 reviews |
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10 of 11 found the following review helpful:
a summary of research on support vector machines May 16, 2000
By Random Thoughts
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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