429 search results - page 3 / 86 » Unsupervised feature selection for principal components anal... |
JMLR
2012
11 years 10 months ago
2012
Traditional tensor decompositions such as the CANDECOMP / PARAFAC (CP) and Tucker decompositions yield higher-order principal components that have been used to understand tensor d...
ICPR
2002
IEEE
14 years 8 months ago
2002
IEEE
Content-based image retrieval can be dramatically improved by providing a good initial database overview to the user. To address this issue, we present in this paper the Adaptive ...
BMCBI
2010
13 years 7 months ago
2010
Background: As a novel cancer diagnostic paradigm, mass spectroscopic serum proteomic pattern diagnostics was reported superior to the conventional serologic cancer biomarkers. Ho...
SDM
2010
SIAM
13 years 6 months ago
2010
SIAM
A popular approach for dimensionality reduction and data analysis is principal component analysis (PCA). A limiting factor with PCA is that it does not inform us on which of the o...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...