178 search results - page 9 / 36 » Structured Sparse Principal Component Analysis |
ISBI
2011
IEEE
12 years 11 months ago
2011
IEEE
In imaging genomics, there have been rapid advances in genome-wide, image-wide searches for genes that influence brain structure. Most efforts focus on univariate tests that treat...
SDM
2010
SIAM
13 years 5 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...
SIAMJO
2011
13 years 1 months ago
2011
In this paper we define semidefinite packing programs and describe an algorithm to approximately solve these problems. Semidefinite packing programs arise in many applications s...
JMLR
2012
11 years 10 months ago
2012
We study sparse principal components analysis in the high-dimensional setting, where p (the number of variables) can be much larger than n (the number of observations). We prove o...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
Eigenvalue problems are rampant in machine learning and statistics and appear in the context of classification, dimensionality reduction, etc. In this paper, we consider a cardina...