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» The Kernel Least-Mean-Square Algorithm
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TIP
2008
175views more  TIP 2008»
15 years 3 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...
135
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DSL
2009
15 years 1 months ago
Operator Language: A Program Generation Framework for Fast Kernels
Abstract. We present the Operator Language (OL), a framework to automatically generate fast numerical kernels. OL provides the structure to extend the program generation system Spi...
Franz Franchetti, Frédéric de Mesmay...
175
Voted
JMLR
2010
145views more  JMLR 2010»
14 years 10 months ago
Kernel Partial Least Squares is Universally Consistent
We prove the statistical consistency of kernel Partial Least Squares Regression applied to a bounded regression learning problem on a reproducing kernel Hilbert space. Partial Lea...
Gilles Blanchard, Nicole Krämer
154
Voted
ICCV
2011
IEEE
14 years 3 months ago
A Theory of Coprime Blurred Pairs
We present a new Coprime Blurred Pair (CBP) theory that may benefit a number of computer vision applications. A CBP is constructed by blurring the same latent image with two unkn...
Feng Li, Zijia Li, David Saunders, Jingyi Yu
185
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DAGM
2011
Springer
14 years 3 months ago
Using Landmarks as a Deformation Prior for Hybrid Image Registration
Hybrid registration schemes are a powerful alternative to fully automatic registration algorithms. Current methods for hybrid registration either include the landmark information a...
Marcel Lüthi, Christoph Jud, Thomas Vetter