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» Nonlinear Component Analysis as a Kernel Eigenvalue Problem
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ICML
2007
IEEE
16 years 15 days ago
Dimensionality reduction and generalization
In this paper we investigate the regularization property of Kernel Principal Component Analysis (KPCA), by studying its application as a preprocessing step to supervised learning ...
Sofia Mosci, Lorenzo Rosasco, Alessandro Verri
ICIP
2004
IEEE
16 years 1 months ago
Advances in texture analysis-energy dominant component & multiple hypothesis testing
Modelling textured images as AM-FM functions has been applied during the last years to texture analysis and segmentation tasks. In this paper we present some advances in two direc...
Iasonas Kokkinos, Georgios Evangelopoulos, Petros ...
ICA
2007
Springer
15 years 5 months ago
On Separation of Signal Sources Using Kernel Estimates of Probability Densities
The discussion in this paper revolves around the notion of separation problems. The latter can be thought of as a unifying concept which includes a variety of important problems in...
Oleg V. Michailovich, Douglas Wiens
CVPR
2006
IEEE
16 years 1 months ago
Selecting Principal Components in a Two-Stage LDA Algorithm
Linear Discriminant Analysis (LDA) is a well-known and important tool in pattern recognition with potential applications in many areas of research. The most famous and used formul...
Aleix M. Martínez, Manli Zhu
IJON
2006
169views more  IJON 2006»
14 years 11 months ago
Denoising using local projective subspace methods
In this paper we present denoising algorithms for enhancing noisy signals based on Local ICA (LICA), Delayed AMUSE (dAMUSE) and Kernel PCA (KPCA). The algorithm LICA relies on app...
Peter Gruber, Kurt Stadlthanner, Matthias Böh...