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CS295, Winter 2008: Advanced Methods in Graphical Models

This course is a highly participatory exploration of recent research directions in learning and inference algorithms for probabilistic models, particularly graphical models (Bayes' nets, Markov random fields, et cetera). The class is structured to include both a student-led seminar portion, similar to a reading group but with more week-to-week structure, and a lecture part in which we will cover additional background, extensions and other related material. The course provides the opportunity to read and understand recent work relevant to research in graphical models and machine learning, while giving the course more structure and continuity than a typical seminar or reading group.

Background.

Although the first week or two will provide a brief introduction to graphical models, students are expected to have some basic background, such as one of CS 271, 274-276 or equivalent. If unsure, send me an email or come by my office (BH4066) to discuss your background.

Course format.

You, the student, will have the ability to influence the exact topics we cover. At the first meeting, we will decide on the set and sequence of topics, and students will divide into small groups, each of which will choose one topic for their own. Each week, one group will be responsible for reviewing the literature associated with their topic (with assistance from myself), providing a short written summary beforehand for the rest of the class, and leading a presentation and discussion of the papers during Tuesday class. The Thursday lecture will then proceed to elaborate in more depth, covering extensions or other closely related topics, or giving more background and details, depending on the subject. It is possible (even likely) that we will not make it through all the topics; priority will be given to "Tuesday" topics, with additional coverage by myself during the lecture portion on Thursday if necessary.

Note: although there are one or more papers associated with each day's lecture, they should be considered (non-required) supplemental reading -- primary reading and preparation for the week come from the student-prepared summaries for Tuesday.

Topics.

A selection of possible topics follows; these are subject to change and re-arrangment in the future. If you have additional ideas or suggestions for topics you'd like to see covered, let me know by email or in person and we will discuss them on the first day.