Course # 41430 Section Number 1 Day(s) Tu- Th Time(s) 3:30pm-4:50pm Term Fall 2024 Course Instructor Guillaume Pouliot Syllabus Syllabus 9/18/24 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: Kadin Kessler, MPP Class of 2026 Thu., December 12, 2024 Alumni Profile: Peter Beniaris, Policy Analytics Credential’24 Tue., December 10, 2024 China Career Pathways Program Helps Students Nab That Post-Degree Job Tue., December 10, 2024 Upcoming Events More events Harris Winter Campus Visit Mon., December 16, 2024 | 10:30 AM 1307 E 60th St Chicago, IL 60637 United States Policy Research and Innovation Bootcamp (PRIB): Mini Class with Benjamin Krause Tue., December 17, 2024 | 7:30 PM UChicago Harris Information Session - Joint Degree Programs Wed., December 18, 2024 | 12:00 PM