21 search results - page 1 / 5 » Budgeted Distribution Learning of Belief Net Parameters |
73
Voted
ICML
2010
IEEE
15 years 2 months ago
2010
IEEE
118
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UAI
2004
15 years 2 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...
117
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UAI
2000
15 years 2 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...
119
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AMAI
2004
Springer
15 years 6 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
16 years 2 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...