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» Kernel Methods for Pattern Analysis
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CVPR
2005
IEEE
14 years 9 months ago
Applying Neighborhood Consistency for Fast Clustering and Kernel Density Estimation
Nearest neighborhood consistency is an important concept in statistical pattern recognition, which underlies the well-known k-nearest neighbor method. In this paper, we combine th...
Kai Zhang, Ming Tang, James T. Kwok
CSDA
2010
139views more  CSDA 2010»
13 years 7 months ago
Detecting influential observations in Kernel PCA
Kernel Principal Component Analysis extends linear PCA from a Euclidean space to any reproducing kernel Hilbert space. Robustness issues for Kernel PCA are studied. The sensitivit...
Michiel Debruyne, Mia Hubert, Johan Van Horebeek
RECOMB
2004
Springer
14 years 29 days ago
Application of Kernel Method to Reveal Subtypes of TF Binding Motifs
Transcription factor binding sites often contain several subtypes of sequences that follow not just one but several different patterns. We developed a novel sensitive method based ...
Alexander E. Kel, Yuri Tikunov, Nico Voss, Jü...
IEICET
2007
57views more  IEICET 2007»
13 years 7 months ago
A Learning Algorithm of Boosting Kernel Discriminant Analysis for Pattern Recognition
Shinji Kita, Seiichi Ozawa, Satoshi Maekawa, Shige...
PR
2007
139views more  PR 2007»
13 years 7 months ago
Learning the kernel matrix by maximizing a KFD-based class separability criterion
The advantage of a kernel method often depends critically on a proper choice of the kernel function. A promising approach is to learn the kernel from data automatically. In this p...
Dit-Yan Yeung, Hong Chang, Guang Dai