Events
Colloquium
FDS Colloquium: Munther Dahleh (MIT), “Learning multiple models with limited and sparse data”
Abstract: In this talk, we address the challenge of learning models for a large number of agents when only limited data is available for […]
Research in Motion: Nicole Immorlica (Microsoft Research) “The Economic Impacts of Generative AI”
Co-sponsored by CADMY, FDS, and Tsai CITY Speaker bio: Nicole Immorlica is a senior principal researcher at Microsoft Research New England (MSR NE) where […]
FDS Colloquium: Elliot Paquette (McGill), “High-dimensional Optimization with Applications to Compute-Optimal Neural Scaling Laws”
Abstract: Given the massive scale of modern ML models, we now only get a single shot to train them effectively. This restricts our ability to test multiple […]
FDS Colloquium: Richard Samworth (Cambridge), “How should we do linear regression?”
Cohosted by Yale School of Public Health Abstract: In the context of linear regression, we construct a data-driven convex loss function with respect to […]
Page 1 of 1
