248 search results - page 16 / 50 » Learning the Structure of Dynamic Probabilistic Networks |
104
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VLSID
2005
IEEE
16 years 5 days ago
2005
IEEE
We propose a novel, non-simulative, probabilistic model for switching activity in sequential circuits, capturing both spatio-temporal correlations at internal nodes and higher ord...
NN
2007
Springer
14 years 11 months ago
2007
Springer
Echo State Networks (ESNs) have been shown to be effective for a number of tasks, including motor control, dynamic time series prediction, and memorizing musical sequences. Howeve...
119
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ICML
2004
IEEE
16 years 18 days ago
2004
IEEE
Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when lear...
ICML
2007
IEEE
16 years 19 days ago
2007
IEEE
The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we ext...
ISNN
2007
Springer
15 years 6 months ago
2007
Springer
A novel online dynamic value system for machine learning is proposed in this paper. The proposed system has a dual network structure: data processing network (DPN) and information ...