4947 search results - page 222 / 990 » Learning Module Networks |
126
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KDD
2006
ACM
16 years 3 months ago
2006
ACM
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
140
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AMAI
2004
Springer
15 years 8 months ago
2004
Springer
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
151
Voted
KDD
2009
ACM
16 years 3 months ago
2009
ACM
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
138
Voted
AUSAI
2004
Springer
15 years 8 months ago
2004
Springer
The K-means Fast Learning Artificial Neural Network (KFLANN) is a small neural network bearing two types of parameters, the tolerance, δ and the vigilance, µ. In previous papers,...
113
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UAI
1998
15 years 4 months ago
1998
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...