148 search results - page 4 / 30 » Discriminative parameter learning for Bayesian networks |
ICPR
2008
IEEE
15 years 10 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...
ICML
2007
IEEE
15 years 10 months ago
2007
IEEE
We present a method for parameter learning in relational Bayesian networks (RBNs). Our approach consists of compiling the RBN model into a computation graph for the likelihood fun...
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...
109
click to vote
JMLR
2012
13 years 2 days ago
2012
The expectation maximization (EM) algorithm is a popular algorithm for parameter estimation in models with hidden variables. However, the algorithm has several non-trivial limitat...