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UAI
1998
15 years 8 months ago
Learning From What You Don't Observe
The process of diagnosis involves learning about the state of a system from various observations of symptoms or findings about the system. Sophisticated Bayesian (and other) algor...
Mark A. Peot, Ross D. Shachter
WSC
2000
15 years 8 months ago
Interactive Web-based animations for teaching and learning
Web-based study resources can be viewed as a basic requirement in order to remain a competitive player on a more and more globalised educational market. For that reason it is gett...
Michael Syrjakow, Jörg Berdux, Helena Szczerb...
AAAI
1994
15 years 8 months ago
Learning to Select Useful Landmarks
To navigate effectively, an autonomous agent must be able to quickly and accurately determine its current location. Given an initial estimate of its position (perhaps based on dea...
Russell Greiner, Ramana Isukapalli
UAI
1993
15 years 8 months ago
Using Causal Information and Local Measures to Learn Bayesian Networks
In previous work we developed a method of learning Bayesian Network models from raw data. This method relies on the well known minimal description length (MDL) principle. The MDL ...
Wai Lam, Fahiem Bacchus
CEC
2010
IEEE
15 years 7 months ago
Two novel Ant Colony Optimization approaches for Bayesian network structure learning
Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
Yanghui Wu, John A. W. McCall, David W. Corne