339 search results - page 3 / 68 » Approximate Inference in Probabilistic Graphical Models with... |
OSDI
2008
ACM
14 years 7 months ago
2008
ACM
Although queueing models have long been used to model the performance of computer systems, they are out of favor with practitioners, because they have a reputation for requiring u...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Variational inference methods, including mean field methods and loopy belief propagation, have been widely used for approximate probabilistic inference in graphical models. While ...
UAI
1998
13 years 8 months ago
1998
There is evidence that the numbers in probabilistic inference don't really matter. This paper considers the idea that we can make a probabilistic model simpler by making fewe...
AI
2011
Springer
13 years 2 months ago
2011
Springer
The paper focuses on developing effective importance sampling algorithms for mixed probabilistic and deterministic graphical models. The use of importance sampling in such graphi...
SEMWEB
2005
Springer
14 years 26 days ago
2005
Springer
Probabilistic inference will be of special importance when one needs to know how much we can say with what all we know given new observations. Bayesian Network is a graphical prob...