25 search results - page 1 / 5 » Learning Bounded Treewidth Bayesian Networks |
NIPS
2008
13 years 6 months ago
2008
With the increased availability of data for complex domains, it is desirable to learn Bayesian network structures that are sufficiently expressive for generalization while at the ...
ECAI
2010
Springer
13 years 4 months ago
2010
Springer
Abstract. Algorithms for probabilistic inference in Bayesian networks are known to have running times that are worst-case exponential in the size of the network. For networks with ...
AAAI
2006
13 years 6 months ago
2006
The MAP (maximum a posteriori hypothesis) problem in Bayesian networks is to find the most likely states of a set of variables given partial evidence on the complement of that set...
SODA
2001
ACM
13 years 6 months ago
2001
ACM
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
UAI
2004
13 years 6 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 ...