131 search results - page 7 / 27 » Global Conditioning for Probabilistic Inference in Belief Ne... |
HIS
2004
13 years 8 months ago
2004
Many researchers have observed that neurons process information in an imprecise manner - if a logical inference emerges from neural computation, it is inexact at best. Thus, there...
ECAI
2010
Springer
13 years 8 months ago
2010
Springer
We investigate probabilistic propositional logic as a way of expressing and reasoning about uncertainty. In contrast to Bayesian networks, a logical approach can easily cope with i...
AI
2002
Springer
13 years 7 months ago
2002
Springer
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
AI
2006
Springer
13 years 11 months ago
2006
Springer
Abstract. A conditioning graph (CG) is a graphical structure that attempt to minimize the implementation overhead of computing probabilities in belief networks. A conditioning grap...
UAI
1997
13 years 8 months ago
1997
This paper describes a class ofprobabilistic approximation algorithms based on bucket elimination which o er adjustable levels of accuracy ande ciency. We analyzethe approximation...