1340 search results - page 70 / 268 » Structure learning of Bayesian networks using constraints |
101
click to vote
AAAI
2006
15 years 1 months ago
2006
Previous work in knowledge transfer in machine learning has been restricted to tasks in a single domain. However, evidence from psychology and neuroscience suggests that humans ar...
CONNECTION
2004
14 years 11 months ago
2004
: High capacity associative neural networks can be built from networks of perceptrons, trained using simple perceptron training. Such networks perform much better than those traine...
UAI
2003
15 years 1 months ago
2003
Precision achieved by stochastic sampling algorithms for Bayesian networks typically deteriorates in face of extremely unlikely evidence. To address this problem, we propose the E...
ICANN
2009
Springer
15 years 6 months ago
2009
Springer
The best recent supervised sequence learning methods use gradient descent to train networks of miniature nets called memory cells. The most popular cell structure seems somewhat ar...
ICANN
2009
Springer
15 years 4 months ago
2009
Springer
Neural networks and other sophisticated machine learning algorithms frequently miss simple solutions that can be discovered by a more constrained learning methods. Transition from ...