1340 search results - page 67 / 268 » Structure learning of Bayesian networks using constraints |
192
click to vote
NIPS
2004
15 years 7 months ago
2004
We describe an approach to building brain-computer interfaces (BCI) based on graphical models for probabilistic inference and learning. We show how a dynamic Bayesian network (DBN...
187
click to vote
COLING
2000
15 years 7 months ago
2000
In this paper, word sense dismnbiguation (WSD) accuracy achievable by a probabilistic classifier, using very milfimal training sets, is investigated. \Ve made the assuml)tiou that...
182
click to vote
UAI
2008
15 years 7 months ago
2008
Graphical models are usually learned without regard to the cost of doing inference with them. As a result, even if a good model is learned, it may perform poorly at prediction, be...
222
click to vote
COLT
1994
Springer
15 years 10 months ago
1994
Springer
Inductive Logic Programming (ILP) involves the construction of first-order definite clause theories from examples and background knowledge. Unlike both traditional Machine Learnin...
176
click to vote
PPSN
2004
Springer
15 years 11 months ago
2004
Springer
Two ideas taken from Bayesian optimization and classifier systems are presented for personnel scheduling based on choosing a suitable scheduling rule from a set for each person’s...