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: Eltjana Plaku, MPP Class of 2026 Thu., October 17, 2024 'Dobbs Dads': The Sleeper Coalition That Could Turn out for Kamala Harris Wed., October 16, 2024 Illinois officials battle misinformation to protect integrity of November election Tue., October 15, 2024 Upcoming Events More events 2024 Pearson Global Forum | Negotiation and Agreement Fri., October 18, 2024 | 8:00 AM 1201 East 60th Street Chicago, IL 60637 United States Coffee Chat in Boston, MA Fri., October 18, 2024 | 8:30 AM The Well Coffee House 212 Washington St Boston, MA 02108 United States Get to Know Harris! Public Sector Scholarship Fri., October 18, 2024 | 12:00 PM