502 search results - page 11 / 101 » Principal Component Analysis for Sparse High-Dimensional Dat... |
ICASSP
2009
IEEE
13 years 11 months ago
2009
IEEE
We consider principal component analysis (PCA) in decomposable Gaussian graphical models. We exploit the prior information in these models in order to distribute its computation. ...
IJCNN
2006
IEEE
14 years 1 months ago
2006
IEEE
Abstract— In this paper, we propose a new nonlinear principal component analysis based on a generalized correlation function which we call correntropy. The data is nonlinearly tr...
MLDM
2009
Springer
14 years 2 months ago
2009
Springer
This paper describes recognition of emotions of an unkown person during natural walking. As gait data is redundant, high dimensional and variable, effective feature extraction is ...
BMCBI
2011
12 years 11 months ago
2011
Background: High-throughput functional genomics technologies generate large amount of data with hundreds or thousands of measurements per sample. The number of sample is usually m...
ICDM
2008
IEEE
14 years 2 months ago
2008
IEEE
