181 search results - page 8 / 37 » Learning bayesian networks consistent with the optimal branc... |
ML
2006
ACM
13 years 7 months ago
2006
ACM
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
Recently, the margin criterion has been successfully used for parameter optimization in graphical models. We introduce maximum margin based structure learning for Bayesian network...
ICML
2000
IEEE
14 years 8 months ago
2000
IEEE
Although Bayesian model averaging is theoretically the optimal method for combining learned models, it has seen very little use in machine learning. In this paper we study its app...
ICPR
2008
IEEE
14 years 1 months ago
2008
IEEE
This paper describes a new approach to unify constraints on parameters with training data to perform parameter estimation in Bayesian networks of known structure. The method is ge...
IJAR
2006
13 years 7 months ago
2006
We consider the problem of learning the parameters of a Bayesian network from data, while taking into account prior knowledge about the signs of influences between variables. Such...