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» Tangent Distance Kernels for Support Vector Machines
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JCP
2006
102views more  JCP 2006»
13 years 7 months ago
Efficient Formulations for 1-SVM and their Application to Recommendation Tasks
The present paper proposes new approaches for recommendation tasks based on one-class support vector machines (1-SVMs) with graph kernels generated from a Laplacian matrix. We intr...
Yasutoshi Yajima, Tien-Fang Kuo
CAIP
2009
Springer
210views Image Analysis» more  CAIP 2009»
13 years 11 months ago
Shape Classification Using a Flexible Graph Kernel
The medial axis being an homotopic transformation, the skeleton of a 2D shape corresponds to a planar graph having one face for each hole of the shape and one node for each junctio...
François-Xavier Dupé, Luc Brun
ICML
2003
IEEE
14 years 8 months ago
Kernel PLS-SVC for Linear and Nonlinear Classification
A new method for classification is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by a ...
Roman Rosipal, Leonard J. Trejo, Bryan Matthews
ICIAP
2009
ACM
14 years 8 months ago
A New Generative Feature Set Based on Entropy Distance for Discriminative Classification
Abstract. Score functions induced by generative models extract fixeddimensions feature vectors from different-length data observations by subsuming the process of data generation, ...
Alessandro Perina, Marco Cristani, Umberto Castell...
CIDM
2007
IEEE
13 years 11 months ago
Efficient Kernel-based Learning for Trees
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...