Our upcoming event for the Statistics Department Colloquium Series is scheduled for Monday, September 30 from 12:00 – 1:00pm (ET) and will be an in-person presentation Science Center Rm. 316. Lunch will be provided to guests following the talk. This week's speaker will be Song Mei of the Statistics and Electrical Engineering and Computer Science departments at U.C. Berkeley.
Title: Revisiting neural network approximation theory in the age of generative AI
Abstract: Textbooks on deep learning theory primarily perceive neural networks as universal function approximators. While this classical viewpoint is fundamental, it inadequately explains the impressive capabilities of modern generative AI models such as language models and diffusion models. This talk puts forth a refined perspective: neural networks often serve as algorithm approximators, going beyond mere function approximation. I will explain how this refined perspective offers a deeper insight into the success of modern generative AI models.
LOCATION:Science Center 316 STATUS:CONFIRMED DTSTART:20240930T160000Z DTEND:20240930T170000Z END:VEVENT END:VCALENDAR