CSCI699: Topics in Learning and Game Theory (Fall 2017)

Basic information


Schedule by Week

Course Description

This course will examine recent research trends at the interface of learning and game theory. Topics will include online learning and its connection to game equilibria, the design of auctions and mechanisms from data, computational aspects of econometrics, learning from strategic data sources, etc. This class will be targeted at PhD students. Mathematical maturity, as well as research experience in computer science and/or data science is strongly recommended.



Requirements and Grading

Late Homework Policy: Students will be allowed 4 late days for homework, to be used in integer amounts and distributed as the student sees fit. Additional late days will each result in a deduction of 10% of the grade of the corresponding assignment.


This is a topics course, and therefore we will refer to many sources including books and papers; in the vast majority of cases those sources will be available online, and will be linked on the course homepage.