187 search results - page 11 / 38 » Nonlinear Component Analysis as a Kernel Eigenvalue Problem |
109
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IJCNN
2006
IEEE
15 years 5 months ago
2006
IEEE
With very noisy data, having plentiful samples eliminates overfitting in nonlinear regression, but not in nonlinear principal component analysis (NLPCA). To overcome this problem...
111
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ACCV
2007
Springer
15 years 5 months ago
2007
Springer
A novel kernel discriminant transformation (KDT) algorithm based on the concept of canonical differences is presented for automatic face recognition applications. For each individu...
111
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ECCV
2004
Springer
16 years 1 months ago
2004
Springer
Abstract. We present a method for learning feature descriptors using multiple images, motivated by the problems of mobile robot navigation and localization. The technique uses the ...
103
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ECCV
2004
Springer
15 years 5 months ago
2004
Springer
The null space of the within-class scatter matrix is found to express most discriminative information for the small sample size problem (SSSP). The null space-based LDA takes full ...
105
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ICPR
2006
IEEE
16 years 21 days ago
2006
IEEE
In this paper, a multilinear formulation of the popular Principal Component Analysis (PCA) is proposed, named as multilinear PCA (MPCA), where the input can be not only vectors, b...