53 search results - page 8 / 11 » Expectation Propagation for approximate Bayesian inference |
NIPS
2007
13 years 9 months ago
2007
Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
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 ...
JMLR
2010
13 years 2 months ago
2010
Round-based games are an instance of discrete planning problems. Some of the best contemporary game tree search algorithms use random roll-outs as data. Relying on a good policy, ...
CORR
2012
Springer
12 years 3 months ago
2012
Springer
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
SIGMOD
2010
ACM
14 years 15 days ago
2010
ACM
Real-world databases often contain syntactic and semantic errors, in spite of integrity constraints and other safety measures incorporated into modern DBMSs. We present ERACER, an...