305 search results - page 56 / 61 » Bayesian Learning of Markov Network Structure |
NIPS
1998
13 years 9 months ago
1998
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
CORR
2011
Springer
12 years 11 months ago
2011
Springer
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. de nite clause programs containing probabilistic facts with a ...
BMCBI
2010
13 years 7 months ago
2010
Background: Chow and Liu showed that the maximum likelihood tree for multivariate discrete distributions may be found using a maximum weight spanning tree algorithm, for example K...
CVIU
2008
13 years 7 months ago
2008
A key problem in video content analysis using dynamic graphical models is to learn a suitable model structure given some observed visual data. We propose a Completed Likelihood AI...
CIVR
2003
Springer
14 years 28 days ago
2003
Springer
The most expressive way humans display emotions is through facial expressions. In this work we report on several advances we have made in building a system for classification of f...