1521 search results - page 45 / 305 » A learning model for oscillatory networks |
UAI
2003
13 years 10 months ago
2003
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
ESANN
2007
13 years 10 months ago
2007
Abstract. As potential candidates for human cognition, connectionist models of sentence processing must learn to behave systematically by generalizing from a small traning set. It ...
HICSS
2005
IEEE
14 years 2 months ago
2005
IEEE
Discourse, a form of collaborative learning [44], is one of the most widely used methods of teaching and learning in the online environment. Particularly in large courses, discour...
IJAR
2006
13 years 8 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...
AAAI
2008
13 years 10 months ago
2008
Modern Bayesian Network learning algorithms are timeefficient, scalable and produce high-quality models; these algorithms feature prominently in decision support model development...