12 search results - page 2 / 3 » On Sparse Nonparametric Conditional Covariance Selection |
TSP
2010
12 years 11 months ago
2010
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
JMLR
2006
13 years 4 months ago
2006
Sparsity or parsimony of statistical models is crucial for their proper interpretations, as in sciences and social sciences. Model selection is a commonly used method to find such...
PAMI
2006
13 years 4 months ago
2006
Three-dimensional appearance models consisting of spatially varying reflectance functions defined on a known shape can be used in analysis-by-synthesis approaches to a number of vi...
MA
2010
Springer
13 years 3 months ago
2010
Springer
: Semiparametric linear transformation models have received much attention due to its high flexibility in modeling survival data. A useful estimating equation procedure was recent...
TCBB
2010
13 years 3 months ago
2010
—Gene expression data usually contain a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best...