156 search results - page 7 / 32 » Generalized Principal Component Analysis (GPCA) |
ADBIS
2003
Springer
14 years 21 days ago
2003
Springer
Recent research has shown the integration of multiple classifiers to be one of the most important directions in machine learning and data mining. It was shown that, for an ensemble...
ISNN
2009
Springer
14 years 2 months ago
2009
Springer
Abstract. Nonlinear component analysis is a popular nonlinear feature extraction method. It generally uses eigen-decomposition technique to extract the principal components. But th...
PAMI
2012
11 years 10 months ago
2012
— Over the last century, Component Analysis (CA) methods such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Canonical Correlation Analysis (CCA), Lap...
NIPS
2003
13 years 8 months ago
2003
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...
KDD
2007
ACM
14 years 7 months ago
2007
ACM
We present a class of richly structured, undirected hidden variable models suitable for simultaneously modeling text along with other attributes encoded in different modalities. O...