921 search results - page 41 / 185 » Kernel Principal Component Analysis |
NIPS
2000
13 years 9 months ago
2000
An eigenvalue method is developed for analyzing periodic structure in speech. Signals are analyzed by a matrix diagonalization reminiscent of methods for principal component analy...
ICCV
2005
IEEE
14 years 9 months ago
2005
IEEE
In recent years Kernel Principal Component Analysis (Kernel PCA) has gained much attention because of its ability to capture nonlinear image features, which are particularly impor...
ICCV
2005
IEEE
14 years 9 months ago
2005
IEEE
Recently there has been a lot of interest in geometrically motivated approaches to data analysis in high dimensional spaces. We consider the case where data is drawn from sampling...
CVPR
2003
IEEE
14 years 9 months ago
2003
IEEE
When performing subspace modelling of data using Principal Component Analysis (PCA) it may be desirable to constrain certain directions to be more meaningful in the context of the...
JMLR
2010
13 years 2 months ago
2010
Bayesian principal component analysis (BPCA), a probabilistic reformulation of PCA with Bayesian model selection, is a systematic approach to determining the number of essential p...