150 search results - page 19 / 30 » Modelling Multiagent Bayesian Networks with Inclusion Depend... |
JETAI
1998
13 years 7 months ago
1998
Graphical structures such as Bayesian networks or Markov networks are very useful tools for representing irrelevance or independency relationships, and they may be used to e cientl...
JMLR
2010
13 years 2 months ago
2010
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
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...
TASE
2008
IEEE
13 years 7 months ago
2008
IEEE
In this paper, we focus on mechanism design for single leader Stackelberg problems, which are a special case of hierarchical decision making problems in which a distinguished agent...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the dependency structure than directed graphical mode...