277 search results - page 2 / 56 » Active Learning for Structure in Bayesian Networks |
CVPR
2004
IEEE
14 years 7 months ago
2004
IEEE
Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...
ITRE
2005
IEEE
13 years 11 months ago
2005
IEEE
A Bayesian network model is a popular technique for data mining due to its intuitive interpretation. This paper presents a semantic genetic algorithm (SGA) to learn a complete qual...
IPL
2008
13 years 5 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 6 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...
NIPS
2000
13 years 6 months ago
2000
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...