Full-Day Course on Uncertain Reasoning
Twelfth Conference on Uncertainty in Artificial Intelligence
This one-day course on principles and applications of uncertain
reasoning will be given on Wednesday, July 31 (the day before the
start of the main UAI 96 conference) at Reed College. Click here
for summaries of the course sessions. Registration information for
the course will be posted with conference registration information.
Introduction and Goals
Eric Horvitz and Finn Jensen
Session I. Foundations of Uncertainty: 8:35-11:00am
- Foundations of Probability and Utility
Instructor: Ross Shachter
Break
- Beyond probability: Alternative Formalisms
Instructor: Prakash Shenoy
- Review and Questions
(Shachter and Shenoy)
Session II. Inference Algorithms for Belief and Action: 11:00-12:45
- Algorithms for probabilistic inference
Instructor: Bruce D'Ambrosio
- Decision making
Instructor: Mark Peot
- Commonalities in inference methods for uncertain reasoning
Instructor: Finn Jensen
- Review and Questions
( D'ambrosio, Jensen, and Peot)
Lunch Break 12:45-2:00pm
Session III. Modeling and Knowledge Acquisition: 2:00-3:15
Instructors: Kathryn Laskey and Michael Shwe
Session IV. Learning Models from Data: 3:15-4:20
- Foundations of Learning Graphical Models
Instructors: Greg Cooper, David Heckerman
- Real-world Application of Learning Methods
Instructor: Wray Buntine
Break
Session V. Uncertain Reasoning in the Real World--Case Studies: 4:30-5:25
Instructors: Eric Horvitz and Mark Peot
Research Directions / UAI 96 Highlights
Details on sessions
Back to UAI-96 Homepage
If you have questions or comments about the UAI-96 Full-Day Course, contact
the UAI-96 Program Cochairs: Eric
Horvitz and Finn
Jensen. For conference arrangements information, please contact
Steve
Hanks.