115 search results - page 13 / 23 » On Axiomatizing Probabilistic Conditional Independencies in ... |
IJPRAI
1998
13 years 7 months ago
1998
We present in this paper a novel method for eliciting the conditional probability matrices needed for a Bayesian network with the help of a neural network. We demonstrate how we c...
IJCAI
2007
13 years 9 months ago
2007
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...
SDM
2008
SIAM
13 years 9 months ago
2008
SIAM
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
ML
2008
ACM
13 years 7 months ago
2008
ACM
Abstract. Recently, there has been an increasing interest in directed probabilistic logical models and a variety of languages for describing such models has been proposed. Although...
IJAR
2010
13 years 6 months ago
2010
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...