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CORR
2008
Springer
77views Education» more  CORR 2008»
15 years 4 months ago
Principal Graphs and Manifolds
In many physical statistical, biological and other investigations it is desirable to approximate a system of points by objects of lower dimension and/or complexity. For this purpo...
Alexander N. Gorban, Andrei Yu. Zinovyev
ISNN
2009
Springer
15 years 11 months ago
Nonlinear Component Analysis for Large-Scale Data Set Using Fixed-Point Algorithm
Abstract. Nonlinear component analysis is a popular nonlinear feature extraction method. It generally uses eigen-decomposition technique to extract the principal components. But th...
Weiya Shi, Yue-Fei Guo
IDA
1998
Springer
15 years 4 months ago
Fast Dimensionality Reduction and Simple PCA
A fast and simple algorithm for approximately calculating the principal components (PCs) of a data set and so reducing its dimensionality is described. This Simple Principal Compo...
Matthew Partridge, Rafael A. Calvo
NIPS
2003
15 years 5 months ago
Extreme Components Analysis
Principal components analysis (PCA) is one of the most widely used techniques in machine learning and data mining. Minor components analysis (MCA) is less well known, but can also...
Max Welling, Felix V. Agakov, Christopher K. I. Wi...
FGR
2004
IEEE
107views Biometrics» more  FGR 2004»
15 years 8 months ago
Intra-Personal Kernel Space for Face Recognition
Intra-personal space modeling proposed by Moghaddam et. al. has been successfully applied in face recognition. In their work the regular principal subspaces are derived from the i...
Shaohua Kevin Zhou, Rama Chellappa, Baback Moghadd...