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» Being Bayesian about Network Structure
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AI
2002
Springer
13 years 9 months ago
The size distribution for Markov equivalence classes of acyclic digraph models
Bayesian networks, equivalently graphical Markov models determined by acyclic digraphs or ADGs (also called directed acyclic graphs or dags), have proved to be both effective and ...
Steven B. Gillispie, Michael D. Perlman
UAI
1998
13 years 11 months ago
Tractable Inference for Complex Stochastic Processes
The monitoring and control of any dynamic system depends crucially on the ability to reason about its current status and its future trajectory. In the case of a stochastic system,...
Xavier Boyen, Daphne Koller
AAAI
2008
14 years 4 days ago
Linking Social Networks on the Web with FOAF: A Semantic Web Case Study
One of the core goals of the Semantic Web is to store data in distributed locations, and use ontologies and reasoning to aggregate it. Social networking is a large movement on the...
Jennifer Golbeck, Matthew Rothstein
AAAI
1998
13 years 11 months ago
Probabilistic Frame-Based Systems
Two of the most important threads of work in knowledge representation today are frame-based representation systems (FRS's) and Bayesian networks (BNs). FRS's provide an ...
Daphne Koller, Avi Pfeffer
NMR
2004
Springer
14 years 3 months ago
Probabilistic reasoning in dynamic multiagent systems
Probabilistic reasoning with multiply sectioned Bayesian networks (MSBNs) has been successfully applied in static domains under the cooperative multiagent paradigm. Probabilistic ...
Xiangdong An, Yang Xiang, Nick Cercone