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» Support Vector Regression Using Mahalanobis Kernels
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ICML
2007
IEEE
14 years 9 months ago
A kernel path algorithm for support vector machines
The choice of the kernel function which determines the mapping between the input space and the feature space is of crucial importance to kernel methods. The past few years have se...
Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky
NIPS
2001
13 years 10 months ago
Online Learning with Kernels
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
BMCBI
2006
125views more  BMCBI 2006»
13 years 8 months ago
Evaluating different methods of microarray data normalization
Background: With the development of DNA hybridization microarray technologies, nowadays it is possible to simultaneously assess the expression levels of thousands to tens of thous...
André Fujita, João Ricardo Sato, Leo...
IGARSS
2010
13 years 6 months ago
Support vector machines regression for estimation of forest parameters from airborne laser scanning data
Estimation of forest stand parameters from airborne laser scanning data relies on the selection of laser metrics sets and numerous field plots for model calibration. In mountainou...
Jean-Matthieu Monnet, Frédéric Berge...
ICML
2010
IEEE
13 years 9 months ago
One-sided Support Vector Regression for Multiclass Cost-sensitive Classification
We propose a novel approach that reduces cost-sensitive classification to one-sided regression. The approach stores the cost information in the regression labels and encodes the m...
Han-Hsing Tu, Hsuan-Tien Lin