Course # 41430 Section Number 1 Day(s) Tu- Th Time(s) 3:30pm-4:50pm Term Fall 2024 Course Instructor Guillaume Pouliot Syllabus Draft Syllabus 8/29/24 This course explores how modern developments in machine learning, AI and statistical learning may be leveraged in order to improve regression analysis and reduced-form econometrics more generally. For instance, we provide a modern, optimization-conscious treatment of linear regression, quantile regression, instrumental variables, and Fréchet-Hoeffding bounds. Throughout, we make an effort to produce methods that remain valid even when models are --as they always are-- misspecified. To produce such regression methods, we fetch tools and results from fields such as linear programming, optimal transport, numerical linear algebra, deep learning and reinforcement learning. Quarter Title Instructor Day(s) Time(s) Syllabus Fall 2024 Modern Methods for Applied Regression Guillaume Pouliot Tuesday, Thursday 3:30pm-4:50pm Syllabus Fall 2024 Modern Methods for Applied Regression Guillaume Pouliot Tuesday, Thursday 5:00pm-6:20pm Syllabus Recent News More news Student Profile: AJ Horkan, BA/MPP Class of 2025 Fri., September 13, 2024 Debate lives up to the hype Wed., September 11, 2024 ‘There’s only bad options’: expert says city hiring freeze is the best of the worst Wed., September 11, 2024 Upcoming Events More events Get to Know Harris! A Virtual Information Session Wed., September 18, 2024 | 8:00 AM Coffee Chat in Madison, WI Wed., September 18, 2024 | 1:00 PM Valencia Coffee 799 University Ave Madison, WI 53715 United States Get to Know Harris! Public Sector Scholarship Fri., September 20, 2024 | 12:00 PM