21 search results - page 1 / 5 » Budgeted Distribution Learning of Belief Net Parameters |
ICML
2010
IEEE
13 years 5 months ago
2010
IEEE
UAI
2004
13 years 6 months ago
2004
A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
UAI
2000
13 years 6 months ago
2000
In this paper we present decomposable priors, a family of priors over structure and parameters of tree belief nets for which Bayesian learning with complete observations is tracta...
AMAI
2004
Springer
13 years 10 months ago
2004
Springer
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
ICML
2006
IEEE
14 years 5 months ago
2006
IEEE
Many of today's best classification results are obtained by combining the responses of a set of base classifiers to produce an answer for the query. This paper explores a nov...