courses:smu:lectures [CourseWare Wiki]

(there was a link to an obsolete model exam here which I deleted; see the exam folder for an up to date one)

Lectures

The lectures are given in English to all students.

L	Date	Lecturer	Contents
1	18.2.	FŽ	A General Framework for Learning
2	25.2.	FŽ	On-Line Learning, Mistake-Bound Learning Model
3	4.3.	FŽ	Batch Learning, PAC Learning model
4	11.3.	FŽ	Learning first-order CNF's
5	18.3.	FŽ	Learning first-order clauses
6	25.3.	FŽ	(lecture 5 cont'd)
7	1.4.	FŽ	Reinforcement learning
8	8.4.	FŽ	(lecture 7 cont'd)
9	15.4.	FŽ	Learning Bayesian networks
-	22.4.	-	Easter Monday
10	29.4.	FŽ	(lecture 9 cont'd)
11	6.5.	OK	Probabilistic Programming, a non-technical introduction, slides: pp.pdf
12	13.5.	OK	Probabilistic Logic Programming, Prof Luc De Raedt's slides: srl-pp-tutorial-wasp-stockholm.pdf, slides 1-42, 75-81
13	20.5.	OK	(lecture 12 cont'd) Prof Luc De Raedt's slides: 74-81, 96-119, additional WMC slides: wmc_intro.pdf

Lecture slides: smu-slides.pdf (primary study material for lectures 1-10). Minor corrections in lecture slides posted on June 14. Re-download if you have an earlier version. Thanks to all students who reported bugs!

Both resources are under construction. Check back regularly for updates.