JMLR Special Issue on Kernel Methods

Introduction to the Special Issue on Kernel Methods     (Kernel Machines Section)
Nello Cristianini, John Shawe-Taylor, Robert C. Williamson; 2(12):95--96, 2001.
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Kernel Partial Least Squares Regression in Reproducing Kernel Hilbert Space    (Kernel Machines Section)
Roman Rosipal, Leonard J. Trejo; 2(12):97--123, 2001.
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Support Vector Clustering     (Kernel Machines Section)
Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladimir Vapnik; 2(12):125--137, 2001.
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revision: Jan 2002
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One-Class SVMs for Document Classification     (Kernel Machines Section)
Larry M. Manevitz, Malik Yousef; 2(12):139--154, 2001.
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Uniform Object Generation for Optimizing One-class Classifiers     (Kernel Machines Section)
David M.J. Tax, Robert P.W. Duin; 2(12):155--173, 2001.
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errata: [pdf] [ps.gz] [ps]

A Generalized Kernel Approach to Dissimilarity-based Classification     (Kernel Machines Section)
Elzbieta Pekalska, Pavel Paclík, Robert P.W. Duin; 2(12):175--211, 2001.
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revision: Nov 2002
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A New Approximate Maximal Margin Classification Algorithm     (Kernel Machines Section)
Claudio Gentile; 2(12):213--242, 2001.
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Efficient SVM Training Using Low-Rank Kernel Representations     (Kernel Machines Section)
Shai Fine, Katya Scheinberg; 2(12):243--264, 2001.
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On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines     (Kernel Machines Section)
Koby Crammer, Yoram Singer; 2(12):265--292, 2001.
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Exact Simplification of Support Vector Solutions     (Kernel Machines Section)
Tom Downs, Kevin E. Gates, Annette Masters; 2(12):293--297, 2001.
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Classes of Kernels for Machine Learning: A Statistics Perspective     (Kernel Machines Section)
Marc G. Genton; 2(12):299--312, 2001.
[abs][pdf] [ps.gz] [ps]




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