Decision Support Systems 2

Autumn 1999

Topic

Date & time

 Room

Responsible

1 

 Discrete Bayesian networks and their Markov properties Tuesday 7 Sep 10:15 C3-204 UK

2 

 Inference in discrete Bayesian networks Tuesday 14 Sep 10:15 C3-204 UK

3 

 Learning about probabilities Tuesday 21 Sep 10:15 C3-204 ML

4 

 Structural learning Tuesday 28 Sep 10:15 C3-204 CBT

5 

 Gradient descent training of Bayesian networks Tuesday 5 Oct 10:15 C3-204 TJ

6 

 The BIFROST learning approach Tuesday 12 Oct 10:15 C3-204 ML

7 

 Temporal modelling in Bayesian networks Tuesday 19 Oct 10:15 C3-204 CBT

8 

 Propagation with conditional Gaussian distributions Thursday 21 Oct 10:15 A6-104 ALM

9 

 Decision networks (influence diagrams) Tuesday 2 Nov 12:30 E1-107 TJ

10 

 Bayesian troubleshooting Tuesday 9 Nov 10:15 B2-109 ML

11 

 Data mining Thursday 11 Nov 10:15 A5-006 CBT

12 

 Markov decision processes Tuesday 16 Nov 10:15 C3-204 UK

13 

 Top-down modelling of Bayesian networks (OOBNs) Tuesday 23 Nov 10:15 C3-204 OB

14 

 Partially observed Markov decision processes (POMDPs) Tuesday 30 Nov 10:15 C3-204 UK

15 

 Game theory Tuesday 7 Dec 10:15 C3-204 TJ

About one half or so of the course will be based on the book of Cowell, Dawid, Lauritzen and Spiegelhalter (1999), Probabilistic Networks and Expert Systems, Springer. Both an official errata sheet and a local unofficial errata sheet (not including the items on the official one) for the book are available.

This page is maintained by Uffe Kjærulff.
Last updated 9 November 1999.