305 search results - page 8 / 61 » Bayesian Learning of Markov Network Structure |
IJCAI
2001
13 years 9 months ago
2001
The task of causal structure discovery from empirical data is a fundamental problem in many areas. Experimental data is crucial for accomplishing this task. However, experiments a...
FLAIRS
2008
13 years 10 months ago
2008
Hidden Markov models are a powerful technique to model and classify temporal sequences, such as in speech and gesture recognition. However, defining these models is still an art: ...
JMLR
2006
13 years 7 months ago
2006
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
FLAIRS
2007
13 years 10 months ago
2007
We present a description of two small audio/visual immersive installations. The main framework is an interactive structure that enables multiple participants to generate jazz impr...
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
Recently, the margin criterion has been successfully used for parameter optimization in graphical models. We introduce maximum margin based structure learning for Bayesian network...