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 Harris Names 2025 Alumni Award Winners Wed., April 02, 2025 Q&A: Robert Kaestner Discusses the How and Why of Potential Medicaid Cuts Tue., April 01, 2025 Professor Joshua Gottlieb Receives ASHEcon Medal Fri., March 28, 2025 Upcoming Events More events Bay Area Alumni Spring Gathering Thu., April 03, 2025 | 5:30 PM Two Pitchers Brewing Company 2344 Webster St Oakland, CA 94612 United States Policy Research and Innovation Bootcamp (PRIB) Information Session: Navigating Your On-Campus Experience Thu., April 03, 2025 | 7:30 PM Harris Campus Visit Wed., April 09, 2025 | 9:30 AM Harris Public Policy - Keller Center The University of Chicago 1307 E. 60th St Chicago, IL 60637 United States
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