1340 search results - page 67 / 268 » Structure learning of Bayesian networks using constraints |
110
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NIPS
2004
15 years 1 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...
122
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COLING
2000
15 years 1 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...
106
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UAI
2008
15 years 1 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...
147
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COLT
1994
Springer
15 years 3 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...
100
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PPSN
2004
Springer
15 years 5 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...