921 search results - page 12 / 185 » Kernel Principal Component Analysis |
TIT
2002
13 years 7 months ago
2002
Principal curves, like principal components, are a tool used in multivariate analysis for ends like feature extraction. Defined in their original form, principal curves need not ex...
ICASSP
2010
IEEE
13 years 7 months ago
2010
IEEE
The importance estimation problem (estimating the ratio of two probability density functions) has recently gathered a great deal of attention for use in various applications, e.g....
WEBI
2005
Springer
14 years 1 months ago
2005
Springer
In this work, we show that Kleinberg’s hubs and authorities model (HITS) is simply Principal Components Analysis (PCA; maybe the most widely used multivariate statistical analys...
JMLR
2006
13 years 7 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...
AAAI
2004
13 years 9 months ago
2004
Based on the probabilistic reformulation of principal component analysis (PCA), we consider the problem of determining the number of principal components as a model selection prob...