34 search results - page 1 / 7 » Structural-EM for learning PDG models from incomplete data |
IJAR
2010
13 years 3 months ago
2010
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
UAI
1998
13 years 5 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...
IJAR
2006
13 years 4 months ago
2006
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
KDD
2012
ACM
11 years 7 months ago
2012
ACM
Incomplete data present serious problems when integrating largescale brain imaging data sets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiativ...
ECML
2007
Springer
13 years 10 months ago
2007
Springer
Abstract. Existing relational learning approaches usually work on complete relational data, but real-world data are often incomplete. This paper proposes the MGDA approach to learn...