(Winter 2021) CS 510/610 - Topic on probabilistic graphical models


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  • Syllabus: PDF.
  • Instructor: Prof. Fang Song
  • Email: fsong “AT” pdx.edu. Start your email subject line with “w21-5610-pgm”.
  • Lectures: TR 12:00 - 13:15, remotely via Zoom.
  • Office hours: F 10 - 11am, remotely via zoom.
  • Zoom links: Check “Schedule” page. Also check “PSU Classes” calendar under your PSU Google Suite.
  • Overview: This course will introduce probabilistic graphical models and investigate emerging applications. Graphical models bring together graph theory and probability theory, and provide a flexible framework for modeling probabilistic distributions with complex dependencies. This course will cover the key formalisms and main techniques to construct them and to solve optimization and learning problems.
  • Prerequisite: You must be comfortable with reading and writing mathematical proofs. Familiarity with algorithm analysis, linear algebra, and basic probability theory is essential.
  • Text: No required text. See Resource page for suggested texts and additional useful materials.