86 search results - page 1 / 18 » Clustering and Feature Selection using Sparse Principal Comp... |
CORR
2007
Springer
13 years 4 months ago
2007
Springer
In this paper, we study the application of sparse principal component analysis (PCA) to clustering and feature selection problems. Sparse PCA seeks sparse factors, or linear combi...
JMLR
2012
11 years 7 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...
ICRA
2008
IEEE
13 years 11 months ago
2008
IEEE
— We present a fast feature selection algorithm suitable for object detection applications where the image being tested must be scanned repeatedly to detected the object of inter...
WACV
2008
IEEE
13 years 11 months ago
2008
IEEE
In recent years, many researchers are studying object categorization problem. It is reported that bag of keypoints approach which is based on local features without topological in...
BMCBI
2010
13 years 4 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...