3607 search results - page 130 / 722 » Learning with structured sparsity |
NIPS
2008
13 years 9 months ago
2008
Covariance estimation for high dimensional vectors is a classically difficult problem in statistical analysis and machine learning. In this paper, we propose a maximum likelihood ...
SDM
2008
SIAM
13 years 9 months ago
2008
SIAM
Bayesian text classifiers face a common issue which is referred to as data sparsity problem, especially when the size of training data is very small. The frequently used Laplacian...
ECCV
2010
Springer
13 years 9 months ago
2010
Springer
Abstract. The sparse representation has been widely used in many areas and utilized for visual tracking. Tracking with sparse representation is formulated as searching for samples ...
PKDD
2010
Springer
13 years 6 months ago
2010
Springer
One of the major strengths of probabilistic topic modeling is the ability to reveal hidden relations via the analysis of co-occurrence patterns on dyadic observations, such as docu...
TIP
2010
13 years 6 months ago
2010
—We present in this paper a general formulation for nonnegative data factorization, called projective nonnegative graph embedding (PNGE), which 1) explicitly decomposes the data ...