TuTh 3.30-5 in HSS 2305B
Office hours Mon 1-3 in EBU3B 4138
CSE 254 is a graduate seminar devoted to recent research on AI
learning methods and applications.
This quarter the theme is inference in graphical models.
Prerequisite: background on graphical models (for instance, my class on probabilistic AI).
In each class meeting, a student will give a talk lasting about 60 minutes presenting a recent technical paper in detail. In questions during the talk, and in the final 20 minutes, all seminar participants will discuss the paper and the issues raised by it.
|September 22||organizational meeting||
|September 27||no meeting||
|September 29||Sanjoy||Presentation guidelines; overview of inference||
|October 4||Antoni||An introduction to variational methods for inference||Jordan, Ghahramani, Jaakkola, Saul||here|
|October 6||Daniel||Large deviation methods for approximate probabilistic inference||Kearns, Saul||here|
|October 11||Evan||Fast approximate energy minimization via graph cuts||Boykov, Veksler, Zabih||here|
|October 13||Nan||What energy functions can be minimized via graph cuts?||Kolmogorov, Zabih||here|
|October 18||Brian||Loopy-belief propagation: an empirical study and Efficient belief propagation for early vision||Murphy, Weiss, Jordan; Felzenszwalb, Huttenlocher||here|
|October 20||Thomas||Understanding belief propagation and its generalizations||Yedidia, Freeman, Weiss||here|
|October 25||Brian||Expectation propagation for approximate Bayesian inference||Minka||here|
|October 27||Buhm||Tree-based reparameterization framework for analysis of sum-product and related algorithms||Wainwright, Jaakkola, Willsky||here|
|November 1||Sanjoy||A review of some information geometry||
|November 3 and 8||Daniel||A variational principle for graphical models||Wainwright, Jordan||here|
|November 10||Evan||MAP estimation via agreement on trees||Wainwright, Jordan, Willsky||here|
|November 15||Thomas||Correctness of local probability propagation in graphical models with loops||Weiss||here|
|November 17||Antoni||Nonparametric belief propagation||Sudderth, Ihler, Freeman, Willsky||here|
|November 22||Nan||Classification problems with pairwise relationships||Kleinberg, Tardos||here|
|November 29||Buhm||Pairwise clustering and graphical models||Shental, Zomet, Hertz, Weiss||
|December 1||Project Presentations||
This is a four unit course in which the work consists of presentations and a project. Guidelines for the term project can be found here. Project reports will be evaluated using these grading criteria. There is a schedule for handing in a detailed project proposal, a draft project report, and then the final report.
The seminar will have no final exam. Letter grades will be based on the presentations and the final project report, but participation in class and the intermediate project deliverables are important also.
Each presentation should be prepared using LaTeX or Powerpoint, and should consist of about 40 slides. You must copy all important equations, diagrams, charts, and tables from the paper into your slides.
The schedule of presentations will be determined as much as possible on Thursday September 22. Here is a list of papers.
If you want to change your presentation date, please arrange a swap
with another student and notify me at least two weeks in advance.