37 search results - page 3 / 8 » On the Concentration of Expectation and Approximate Inferenc... |
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...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
CEC
2007
IEEE
14 years 1 months ago
2007
IEEE
— A sensor network is a collection of wireless devices that are able to monitor physical or environmental conditions. These devices are expected to operate autonomously, be batte...
SIGMETRICS
2010
ACM
13 years 7 months ago
2010
ACM
Abstract Due to complexity and intractability reasons, most of the analytical studies on the reliability of communication paths in mobile ad hoc networks are based on the assumptio...
AAAI
2010
13 years 9 months ago
2010
Many problems require repeated inference on probabilistic graphical models, with different values for evidence variables or other changes. Examples of such problems include utilit...