Join the DSI Foundations of Data Science Center for a day-long event featuring two tutorial-style talks from leading experts. The program will explore the statistical and algorithmic tradeoffs of score-based losses in generative modeling, as well as fresh perspectives on classic problems in learning theory. The tutorials will share how rethinking problem formulations can yield new approaches for tractable and efficient learning.
Speakers:
- Andrej Risteski, Assistant Professor, Machine Learning Department, Carnegie Mellon University
- Ankur Moitra, Norbert Wiener Professor of Mathematics, MIT
Read the abstracts on the DSI website
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Details and Agenda
9:00 AM: Guests are welcome to arrive early for check-In and coffee
9:30 AM - 11:30 AM: Tutorial 1: Andrej Risteski, Carnegie Mellon University
- Title: Towards Understanding the Statistical Landscape of Score-based Losses
11:30 AM - 1:00 PM: Lunch & Networking Break (1 hour)
1:00 PM - 3:00 PM: Tutorial 2: Ankur Moitra, MIT
- Title: Vignettes in Learning Theory
3:00 PM: End
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REGISTRATION DEADLINE: The Columbia Morningside campus is open to the Columbia community. If you do not have an active CUID, the deadline to register is at 12:00 PM the day before the event.
