115 search results - page 2 / 23 » Model Selection Through Sparse Maximum Likelihood Estimation |
PAMI
2010
13 years 5 months ago
2010
—Adapting the hyperparameters of support vector machines (SVMs) is a challenging model selection problem, especially when flexible kernels are to be adapted and data are scarce....
CORR
2010
Springer
13 years 6 months ago
2010
Springer
Gaussian graphical models are of great interest in statistical learning. Because the conditional independencies between different nodes correspond to zero entries in the inverse c...
SIAMMAX
2010
13 years 2 months ago
2010
In this paper, we consider estimating sparse inverse covariance of a Gaussian graphical model whose conditional independence is assumed to be partially known. Similarly as in [5],...
ICIAP
2007
ACM
14 years 7 months ago
2007
ACM
In this paper, a novel learning algorithm for Hidden Markov Models (HMMs) has been devised. The key issue is the achievement of a sparse model, i.e., a model in which all irreleva...
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...