37 search results - page 4 / 8 » Exploring Parallelism in Learning Belief Networks |
DATE
2003
IEEE
14 years 8 days ago
2003
IEEE
Novel reconfigurable computing architectures exploit the inherent parallelism available in many signalprocessing problems. These architectures often consist of networks of compute...
ICML
2009
IEEE
14 years 7 months ago
2009
IEEE
The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free paramete...
SKG
2006
IEEE
14 years 1 months ago
2006
IEEE
This article explores the utility of neural network ensembles in knowledge discovery and integration. A novel neural network ensemble model KBNNE (Knowledge-Based Neural Network E...
PPSN
2004
Springer
14 years 10 days ago
2004
Springer
Bayesian networks (BN) constitute a useful tool to model the joint distribution of a set of random variables of interest. To deal with the problem of learning sensible BN models fr...
IDEAL
2004
Springer
14 years 10 days ago
2004
Springer
Abstract. Multiple classifier systems based on neural networks can give improved generalisation performance as compared with single classifier systems. We examine collaboration in ...