181 search results - page 5 / 37 » Learning bayesian networks consistent with the optimal branc... |
JMLR
2010
13 years 2 months ago
2010
We study the problem of learning an optimal Bayesian network in a constrained search space; skeletons are compelled to be subgraphs of a given undirected graph called the super-st...
NIPS
2008
13 years 8 months ago
2008
Uncertainty is omnipresent when we perceive or interact with our environment, and the Bayesian framework provides computational methods for dealing with it. Mathematical models fo...
NIPS
2000
13 years 8 months ago
2000
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
UAI
2004
13 years 8 months ago
2004
In this paper, we present a Branch and Bound algorithm called QuickBB for computing the treewidth of an undirected graph. This algorithm performs a search in the space of perfect ...
CEC
2010
IEEE
13 years 8 months ago
2010
IEEE
Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...