1023 search results - page 13 / 205 » Graph model selection using maximum likelihood |
ICASSP
2009
IEEE
14 years 2 months ago
2009
IEEE
We propose a convex optimization method for maximum likelihood estimation of autoregressive models, subject to conditional independence constraints. This problem is an extension t...
JMLR
2010
13 years 2 months ago
2010
Composite likelihood methods provide a wide spectrum of computationally efficient techniques for statistical tasks such as parameter estimation and model selection. In this paper,...
EMMCVPR
2001
Springer
13 years 12 months ago
2001
Springer
Abstract. Motion segmentation methods often fail to detect the motions of low textured regions. We develop an algorithm for segmentation of low textured moving objects. While usual...
ICC
2007
IEEE
14 years 1 months ago
2007
IEEE
— Blind and semiblind adaptive schemes are proposed for joint maximum likelihood (ML) channel estimation and data detection for multiple-input multiple-output (MIMO) systems. The...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
Recent work has shown that one can learn the structure of Gaussian Graphical Models by imposing an L1 penalty on the precision matrix, and then using efficient convex optimization...