Advances in kernel methods : support vector learning / edited by Bernhard Schölkopf, Christopher J.C. Burges, Alexander J. Smola

Published: Cambridge, Mass. : MIT Press, [1999]
Copyright Date: ©1999
Physical Description: 1 online resource (vii, 376 pages) : illustrations
Additional Creators: Schölkopf, Bernhard, Burges, Christopher J. C., and Smola, Alexander J.

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Language Note

English.

Contents

Preface -- Introduction to support vector learning -- Roadmap -- Three remarks on the support vector method of function estimation / Valdimir Vapnik -- Generalization performance of support vector machines and other pattern classifiers / Peter Bartlett and John Shawe-Taylor -- Bayesian voting schemes and large margin classifiers / Nello Cristianini and John Shawe-Taylor -- Support vector machines, reproducing kernal Hilbert spaces, and randomized GACV / Grace Wahba -- Geometry and invariance in kernel based methods / Christopher J.C. Burgess -- On the annealed VC entropy for margin classifiers : a statistical mechanics study / Manfred Opper -- Entropy numbers, operators and support vector kernels / Robert C. Williamson, Alex J. Smola and Berhard Schölkopf -- Solving the quadratic programming problem arising in support vector classification / Linda Kaufman -- Making large-scale support vector machine learning practical / Thorsten Joachims -- Fast training of support vector machines using sequential minimal optimization / John C. Platt -- Support vector machines for dynamic reconstruction of a chaotic system / David Mattera and Simon Haykin -- Using support vector machines for time series prediction / Klaus-Robert Müller . [and others] -- Pairwise classification and support vector machines / Ulrich Kressel -- Reducing the run-time complexity in support vector machines / Edgar E. Osuna and Federico Girosi -- Support vector regression with ANOVA decomposition kernels / Mark O. Stitson . [and others] -- Support vector density estimation / Jason Weston . [and others] -- Combining support vector and mathematical programming methods for classification / Kristin P. Bennett -- Kernel principal component analysis / Berhard Schölkopf, Alex J. Smola and Klaus-Robert Müller.

Subject(s)

ISBN

0585128294 (electronic bk.)
9780585128290 (electronic bk.)
9780262194167 (alk. paper)
0262194163 (alk. paper)
9780262283199 (electronic book)
0262283190 (electronic book)

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Bibliography Note

Includes bibliographical references (pages 353-371) and index.

View MARC record | catkey: 43184837