889 search results - page 39 / 178 » Observational Learning in Random Networks |
IJAR
2008
13 years 9 months ago
2008
When an incremental structural learning method gradually modifies a Bayesian network (BN) structure to fit observations, as they are read from a database, we call the process stru...
KIVS
2005
Springer
14 years 2 months ago
2005
Springer
: We develop a model for the distribution of nodes in ring-based DHTs like Chord that position nodes randomly or based on hash-functions. As benefit of our model we get the distri...
ECML
2006
Springer
14 years 1 months ago
2006
Springer
Abstract. Active learning algorithms attempt to accelerate the learning process by requesting labels for the most informative items first. In real-world problems, however, there ma...
SENSYS
2003
ACM
14 years 2 months ago
2003
ACM
We consider dense wireless sensor networks deployed to observe arbitrary random fields. The requirement is to reconstruct an estimate of the random field at a certain collector ...
GECCO
2008
Springer
13 years 10 months ago
2008
Springer
A possible alternative to fine topology tuning for Neural Network (NN) optimization is to use Echo State Networks (ESNs), recurrent NNs built upon a large reservoir of sparsely r...