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» Tangent Distance Kernels for Support Vector Machines
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ICCV
2009
IEEE
13 years 5 months ago
Kernel map compression using generalized radial basis functions
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
Omar Arif, Patricio A. Vela
ACL
2006
13 years 9 months ago
Automatic Learning of Textual Entailments with Cross-Pair Similarities
In this paper we define a novel similarity measure between examples of textual entailments and we use it as a kernel function in Support Vector Machines (SVMs). This allows us to ...
Fabio Massimo Zanzotto, Alessandro Moschitti
JMLR
2008
140views more  JMLR 2008»
13 years 7 months ago
Aggregation of SVM Classifiers Using Sobolev Spaces
This paper investigates statistical performances of Support Vector Machines (SVM) and considers the problem of adaptation to the margin parameter and to complexity. In particular ...
Sébastien Loustau
ML
2002
ACM
146views Machine Learning» more  ML 2002»
13 years 7 months ago
Kernel Matching Pursuit
Matching Pursuit algorithms learn a function that is a weighted sum of basis functions, by sequentially appending functions to an initially empty basis, to approximate a target fu...
Pascal Vincent, Yoshua Bengio
PAKDD
2009
ACM
233views Data Mining» more  PAKDD 2009»
14 years 6 days ago
A Kernel Framework for Protein Residue Annotation
Abstract. Over the last decade several prediction methods have been developed for determining structural and functional properties of individual protein residues using sequence and...
Huzefa Rangwala, Christopher Kauffman, George Kary...