Course: Seminar in Artificial Intelligence
Instructor: Max Welling
Time: Tu-Th: 3.30-4.50 PM
Location: CS 253.
Goals: The main objective of this course is for
the students to be introduced to some of the research
that is being conducted at ICS here in UCI. I have asked a number of faculty
who do research in
areas related to artificial intelligence to either talk about their most
representative work or to send me
an article about their most representative research, which we will treat in
If time allows, some timely
topics in AI and statistics will be studied, in particular approximate
on graphs such as belief propagation, mean field and exact sampling.
Students will be asked study a
paper from the literature and prepare a presentation on a topic related to the
material treated in class.
Homework : To be announced
Sep.28 - M.
Welling: Introduction to graphical models
Sep.30 - M. Welling: Introduction to approximate inference
Vibhav Gogate: More on GBP.
Oct.14 - M. Welling: More on MCMC.
Oct.19 - P.
Gehler: Perfect sampling: coupling from the past (David
MacKay’s book, ch. 32 p.413)
Oct.21 - P. Gehler: Perfect sampling: CFTP (Propp &
– Ian: Population MCMC
Oct.28 – Hal Stern
– Matthias Seeger – Discussion on Gaussian Processes
Nov.04 - cancelled
Prof. P. Baldi
Nov.11 - holiday
Prof. E. Mjolsness
Nov.18 - Elroy
Prof. R. Dechter
Nov.25 - holiday
Prof. D. VanDyk
Dec.02 - Anna
to be scheduled: Ian, Elroy, Anna, Earth.
Grading Criteria: Satisfactory/Unsatisfactory