288 search results - page 24 / 58 » Improving Bayesian Network parameter learning using constrai... |
115
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JMLR
2006
15 years 1 months ago
2006
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
120
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ILP
2005
Springer
15 years 6 months ago
2005
Springer
Recursive loops in a logic program present a challenging problem to the PLP framework. On the one hand, they loop forever so that the PLP backward-chaining inferences would never s...
IWINAC
2007
Springer
15 years 7 months ago
2007
Springer
One of the key points in Estimation of Distribution Algorithms (EDAs) is the learning of the probabilistic graphical model used to guide the search: the richer the model the more ...
103
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ACL
2010
14 years 11 months ago
2010
Most previous work on trainable language generation has focused on two paradigms: (a) using a statistical model to rank a set of generated utterances, or (b) using statistics to i...
140
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COLING
2000
15 years 2 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...