1921 search results - page 227 / 385 » Learning from sensor network data |
GRC
2010
IEEE
14 years 11 months ago
2010
IEEE
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
NECO
2002
14 years 9 months ago
2002
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
IICAI
2003
14 years 11 months ago
2003
Abstract. We introduce a new genetic algorithm approach for learning a Bayesian network structure from data. Our method is capable of learning over all node orderings and structure...
UAI
1998
14 years 11 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...
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CORR
2012
Springer
13 years 5 months ago
2012
Springer
The problem of learning the structure of Bayesian networks from complete discrete data with a limit on parent set size is considered. Learning is cast explicitly as an optimisatio...