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PAMI
2008
200views more  PAMI 2008»
13 years 4 months ago
Principal Component Analysis Based on L1-Norm Maximization
In data-analysis problems with a large number of dimension, principal component analysis based on L2-norm (L2PCA) is one of the most popular methods, but L2-PCA is sensitive to out...
Nojun Kwak
ICIP
2002
IEEE
14 years 6 months ago
Hybrid and parallel face classifier based on artificial neural networks and principal component analysis
We present a hybrid and parallel system based on artificial neural networks for a face invariant classifier and general pattern recognition problems. A set of face features is ext...
Peter V. Bazanov, Tae-Kyun Kim, Seok-Cheol Kee, Sa...
JACM
2011
152views more  JACM 2011»
12 years 7 months ago
Robust principal component analysis?
This paper is about a curious phenomenon. Suppose we have a data matrix, which is the superposition of a low-rank component and a sparse component. Can we recover each component i...
Emmanuel J. Candès, Xiaodong Li, Yi Ma, Joh...
IJCNN
2006
IEEE
13 years 11 months ago
Generalizing Independent Component Analysis for Two Related Data Sets
— We introduce in this paper methods for finding mutually corresponding dependent components from two different but related data sets in an unsupervised (blind) manner. The basi...
Juha Karhunen, Tomas Ukkonen
CVPR
2004
IEEE
14 years 6 months ago
Linear Projection Methods in Face Recognition under Unconstrained Illuminations: A Comparative Study
Face recognition under unconstrained illuminations (FR/I) received extensive study because of the existence of illumination subspace. [2] presented a study on the comparison betwe...
Qi Li, Jieping Ye, Chandra Kambhamettu