305 search results - page 5 / 61 » Bayesian Learning of Markov Network Structure |
JMLR
2010
13 years 2 months ago
2010
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
CVPR
1999
IEEE
14 years 9 months ago
1999
IEEE
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
IPL
2008
13 years 7 months ago
2008
Bayesian Network structures with a maximum in-degree of k can be approximated with respect to a positive scoring metric up to an factor of 1/k. Key words: approximation algorithm,...
UAI
1998
13 years 9 months ago
1998
In recent years there has been a flurry of works on learning Bayesian networks from data. One of the hard problems in this area is how to effectively learn the structure of a beli...
UAI
1997
13 years 9 months ago
1997
Recently several researchers have investigated techniques for using data to learn Bayesian networks containing compact representations for the conditional probability distribution...