120 search results - page 1 / 24 » Convex Principal Feature Selection |
SDM
2010
SIAM
13 years 3 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...
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...
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...
KDD
2008
ACM
14 years 5 months ago
2008
ACM
AMSTERDAM
2009
13 years 2 months ago
2009
The paper presents a statistical evaluation of the typological data about color naming systems across the languages of the world that have been obtained by the World Color Survey....