10 search results - page 2 / 2 » Sparse Density Estimation with l1 Penalties |
SDM
2009
SIAM
14 years 4 months ago
2009
SIAM
We consider the task of performing anomaly detection in highly noisy multivariate data. In many applications involving real-valued time-series data, such as physical sensor data a...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
We consider the problem of fitting a large-scale covariance matrix to multivariate Gaussian data in such a way that the inverse is sparse, thus providing model selection. Beginnin...
TIT
1998
13 years 7 months ago
1998
—Probability models are estimated by use of penalized log-likelihood criteria related to AIC and MDL. The accuracies of the density estimators are shown to be related to the trad...
SDM
2012
SIAM
11 years 9 months ago
2012
SIAM
In this paper, we consider the multi-task sparse learning problem under the assumption that the dimensionality diverges with the sample size. The traditional l1/l2 multi-task lass...
CORR
2010
Springer
13 years 7 months ago
2010
Springer
This paper studies the outlier detection problem from the point of view of penalized regressions. Our regression model adds one mean shift parameter for each of the n data points....