2949 search results - page 35 / 590 » Universal Sparse Modeling |
CORR
2010
Springer
13 years 9 months ago
2010
Springer
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
ML
2002
ACM
13 years 9 months ago
2002
ACM
A widely acknowledged drawback of many statistical modelling techniques, commonly used in machine learning, is that the resulting model is extremely difficult to interpret. A numb...
ICML
2009
IEEE
14 years 10 months ago
2009
IEEE
We consider Gaussian multiresolution (MR) models in which coarser, hidden variables serve to capture statistical dependencies among the finest scale variables. Tree-structured MR ...
BMCBI
2008
13 years 9 months ago
2008
Background: When predictive survival models are built from high-dimensional data, there are often additional covariates, such as clinical scores, that by all means have to be incl...
CORR
2008
Springer
13 years 9 months ago
2008
Springer
This paper presents a hierarchical Bayesian model to reconstruct sparse images when the observations are obtained from linear transformations and corrupted by an additive white Gau...