502 search results - page 22 / 101 » Principal Component Analysis for Sparse High-Dimensional Dat... |
BCB
2010
13 years 3 months ago
2010
We present a new method for identifying gene sets associated with labeled samples, where the labels can be case versus control, or genotype differences. Existing approaches to thi...
ICIP
2004
IEEE
14 years 10 months ago
2004
IEEE
We propose a mixture of multiple linear models, also known as hybrid linear model, for a sparse representation of an image. This is a generalization of the conventional KarhunenLo...
KDD
2004
ACM
14 years 9 months ago
2004
ACM
Recent years have witnessed a dramatic increase in the quantity of image data collected, due to advances in fields such as medical imaging, reconnaissance, surveillance, astronomy...
NIPS
2008
13 years 10 months ago
2008
We present a generative model for performing sparse probabilistic projections, which includes sparse principal component analysis and sparse canonical correlation analysis as spec...
CSDA
2004
13 years 8 months ago
2004
Variable selection consists in identifying a k-subset of a set of original variables that is optimal for a given criterion of adequate approximation to the whole data set. Several...