37 search results - page 3 / 8 » Learning Bounds for a Generalized Family of Bayesian Posteri... |
UAI
2001
13 years 7 months ago
2001
In this paper we present a method of computing the posterior probability of conditional independence of two or more continuous variables from data, examined at several resolutions...
UAI
1997
13 years 7 months ago
1997
Recently several researchers have investigated techniques for using data to learn Bayesian networks containing compact representations for the conditional probability distribution...
UAI
2000
13 years 7 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...
CORR
2012
Springer
12 years 1 months ago
2012
Springer
Bayesian priors offer a compact yet general means of incorporating domain knowledge into many learning tasks. The correctness of the Bayesian analysis and inference, however, lar...
PKDD
2010
Springer
13 years 4 months ago
2010
Springer
In this paper we propose a Bayesian model for multi-task feature selection. This model is based on a generalized spike and slab sparse prior distribution that enforces the selectio...