454 search results - page 15 / 91 » Bayesian learning of measurement and structural models |
KES
2007
Springer
14 years 1 months ago
2007
Springer
According to widely accepted guidelines for self-regulation, the capital requirements of a bank should relate to the level of risk with respect to three different categories. Amon...
ISMDA
2001
Springer
14 years 5 days ago
2001
Springer
In recent years, a number of algorithms have been developed for learning the structure of Bayesian networks from data. In this paper we apply some of these algorithms to a realist...
FLAIRS
2008
13 years 10 months ago
2008
Hidden Markov models are a powerful technique to model and classify temporal sequences, such as in speech and gesture recognition. However, defining these models is still an art: ...
PERCOM
2007
ACM
14 years 7 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 9 months ago
2008
With the increased availability of data for complex domains, it is desirable to learn Bayesian network structures that are sufficiently expressive for generalization while at the ...