241 search results - page 4 / 49 » Parameter learning for relational Bayesian networks |
JMLR
2006
14 years 9 months ago
2006
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
IJCAI
2003
14 years 11 months ago
2003
Bayesian network models are widely used for discriminative prediction tasks such as classification. Usually their parameters are determined using 'unsupervised' methods ...
ICPR
2008
IEEE
15 years 11 months ago
2008
IEEE
When a large amount of data are missing, or when multiple hidden nodes exist, learning parameters in Bayesian networks (BNs) becomes extremely difficult. This paper presents a lea...
ICPR
2008
IEEE
15 years 4 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...
FLAIRS
2006
14 years 11 months ago
2006
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...