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» Nonlinear Component Analysis as a Kernel Eigenvalue Problem
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ICASSP
2009
IEEE
15 years 1 months ago
Principal component analysis in decomposable Gaussian graphical models
We consider principal component analysis (PCA) in decomposable Gaussian graphical models. We exploit the prior information in these models in order to distribute its computation. ...
Ami Wiesel, Alfred O. Hero III
PAMI
2010
192views more  PAMI 2010»
14 years 8 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
ICANN
1997
Springer
15 years 1 months ago
Kernel Principal Component Analysis
A new method for performing a nonlinear form of Principal Component Analysis is proposed. By the use of integral operator kernel functions, one can e ciently compute principal comp...
Bernhard Schölkopf, Alex J. Smola, Klaus-Robe...
SIAMSC
2010
192views more  SIAMSC 2010»
14 years 7 months ago
Adaptive Discontinuous Galerkin Methods for Eigenvalue Problems Arising in Incompressible Fluid Flows
In this article we consider the a posteriori error estimation and adaptive mesh refinement of discontinuous Galerkin finite element approximations of the hydrodynamic stability p...
K. Andrew Cliffe, Edward J. C. Hall, Paul Houston
ICANN
2005
Springer
15 years 3 months ago
Handwritten Digit Recognition with Nonlinear Fisher Discriminant Analysis
Abstract. To generalize the Fisher Discriminant Analysis (FDA) algorithm to the case of discriminant functions belonging to a nonlinear, finite dimensional function space F (Nonli...
Pietro Berkes