Instructor: Bo Waggoner
This advanced graduate-level course will cover a number of topics at the interface of computer science and microeconomics, from a theoretical perspective. Examples of likely topics include online learning, mechanism design for approximate welfare and revenue maximization, information elicitation and aggregation, and/or computational social choice. The course will focus on reading papers and a final project.
Prerequisites: Students should be comfortable with multivariable calculus, linear algebra, probability, and discrete mathematics. Experience with convex or linear optimization and design and analysis of algorithms is very beneficial. Game theory and microeconomics is helpful but will not be assumed.