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» Dimensionality Reduction with Adaptive Kernels
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CVPR
2007
IEEE
14 years 9 months ago
Learning Kernel Expansions for Image Classification
Kernel machines (e.g. SVM, KLDA) have shown state-ofthe-art performance in several visual classification tasks. The classification performance of kernel machines greatly depends o...
Fernando De la Torre, Oriol Vinyals
ADC
2006
Springer
158views Database» more  ADC 2006»
14 years 1 months ago
Dimensionality reduction in patch-signature based protein structure matching
Searching bio-chemical structures is becoming an important application domain of information retrieval. This paper introduces a protein structure matching problem and formulates i...
Zi Huang, Xiaofang Zhou, Dawei Song, Peter Bruza
SDM
2010
SIAM
165views Data Mining» more  SDM 2010»
13 years 9 months ago
Direct Density Ratio Estimation with Dimensionality Reduction
Methods for directly estimating the ratio of two probability density functions without going through density estimation have been actively explored recently since they can be used...
Masashi Sugiyama, Satoshi Hara, Paul von Büna...
PRL
2008
95views more  PRL 2008»
13 years 7 months ago
Semi-supervised learning by search of optimal target vector
We introduce a semi-supervised learning estimator which tends to the first kernel principal component as the number of labeled points vanishes. We show application of the proposed...
Leonardo Angelini, Daniele Marinazzo, Mario Pellic...
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