18 search results - page 2 / 4 » Generating Dependence Structure of Multiply Sectioned Bayesi... |
JMLR
2010
13 years 2 days ago
2010
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
NMR
2004
Springer
13 years 10 months ago
2004
Springer
Probabilistic reasoning with multiply sectioned Bayesian networks (MSBNs) has been successfully applied in static domains under the cooperative multiagent paradigm. Probabilistic ...
PERCOM
2007
ACM
14 years 4 months ago
2007
ACM
Abstract. A major challenge in pervasive computing is to learn activity patterns, such as bathing and cleaning from sensor data. Typical sensor deployments generate sparse datasets...
NIPS
2008
13 years 6 months ago
2008
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
IJAR
2008
13 years 5 months ago
2008
Cooperative multiagent probabilistic inference can be applied in areas such as building surveillance and complex system diagnosis to reason about the states of the distributed unc...