462 search results - page 59 / 93 » Probabilistic Principal Component Analysis for Metabolomic D... |
96
Voted
ICPR
2008
IEEE
15 years 11 months ago
2008
IEEE
Speaker independent feature extraction is a critical problem in speech recognition. Oriented principal component analysis (OPCA) is a potential solution that can find a subspace r...
ICML
2005
IEEE
15 years 10 months ago
2005
IEEE
Recently, several manifold learning algorithms have been proposed, such as ISOMAP (Tenenbaum et al., 2000), Locally Linear Embedding (Roweis & Saul, 2000), Laplacian Eigenmap ...
ICIAP
2003
ACM
15 years 2 months ago
2003
ACM
Principal component analyses (PCA) has been widely used in reduction of the dimensionality of datasets, classification, feature extraction, etc. It has been combined with many oth...
JMLR
2006
14 years 9 months ago
2006
The eigenvalues of the kernel matrix play an important role in a number of kernel methods, in particular, in kernel principal component analysis. It is well known that the eigenva...
PAMI
2007
14 years 9 months ago
2007
—In this paper, we present a new model for deformations of shapes. A pseudolikelihood is based on the statistical distribution of the gradient vector field of the gray level. The...