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» Kernel Principal Component Analysis
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ICDM
2006
IEEE
225views Data Mining» more  ICDM 2006»
10 years 7 months ago
Adaptive Kernel Principal Component Analysis with Unsupervised Learning of Kernels
Choosing an appropriate kernel is one of the key problems in kernel-based methods. Most existing kernel selection methods require that the class labels of the training examples ar...
Daoqiang Zhang, Zhi-Hua Zhou, Songcan Chen
IGARSS
2009
9 years 11 months ago
Kernel Principal Component Analysis for the Construction of the Extended Morphological Profile
Kernel Principal Component Analysis (KPCA) is investigated for feature extraction from hyperspectral remotesensing data. Features extracted using KPCA are used to construct the Ex...
Mathieu Fauvel, Jocelyn Chanussot, Jon Atli Benedi...
COLT
2004
Springer
10 years 6 months ago
Statistical Properties of Kernel Principal Component Analysis
The main goal of this paper is to prove inequalities on the reconstruction error for Kernel Principal Component Analysis. With respect to previous work on this topic, our contribu...
Laurent Zwald, Olivier Bousquet, Gilles Blanchard
ICPR
2006
IEEE
10 years 7 months ago
Regularized Locality Preserving Learning of Pre-Image Problem in Kernel Principal Component Analysis
In this paper, we address the pre-image problem in kernel principal component analysis (KPCA). The preimage problem finds a pattern as the pre-image of a feature vector defined in...
Weishi Zheng, Jian-Huang Lai
ESANN
2003
10 years 2 months ago
Kernel PLS variants for regression
Abstract. We focus on covariance criteria for ļ¬nding a suitable subspace for regression in a reproducing kernel Hilbert space: kernel principal component analysis, kernel partial...
Luc Hoegaerts, Johan A. K. Suykens, Joos Vandewall...
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