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» Support Vector Regression Using Mahalanobis Kernels
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TIP
2008
175views more  TIP 2008»
13 years 8 months ago
Customizing Kernel Functions for SVM-Based Hyperspectral Image Classification
Previous research applying kernel methods such as support vector machines (SVMs) to hyperspectral image classification has achieved performance competitive with the best available ...
Baofeng Guo, Steve R. Gunn, Robert I. Damper, Jame...
BMCBI
2010
135views more  BMCBI 2010»
13 years 9 months ago
Detecting disease associated modules and prioritizing active genes based on high throughput data
Background: The accumulation of high-throughput data greatly promotes computational investigation of gene function in the context of complex biological systems. However, a biologi...
Yu-Qing Qiu, Shi-Hua Zhang, Xiang-Sun Zhang, Luona...
AIIA
2007
Springer
14 years 26 days ago
Advanced Tree-Based Kernels for Protein Classification
One of the aims of modern Bioinformatics is to discover the molecular mechanisms that rule the protein operation. This would allow us to understand the complex processes involved i...
Elisa Cilia, Alessandro Moschitti
ICML
2007
IEEE
14 years 9 months ago
More efficiency in multiple kernel learning
An efficient and general multiple kernel learning (MKL) algorithm has been recently proposed by Sonnenburg et al. (2006). This approach has opened new perspectives since it makes ...
Alain Rakotomamonjy, Francis Bach, Stéphane...
PAMI
2010
192views more  PAMI 2010»
13 years 7 months ago
Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCA
—A new formulation for multiway spectral clustering is proposed. This method corresponds to a weighted kernel principal component analysis (PCA) approach based on primal-dual lea...
Carlos Alzate, Johan A. K. Suykens