Misha Belkin is a Professor at Halicioglu Data Science Institute and Computer Science and Engineering Department at UCSD and an Amazon Scholar. His recent work has been concerned with understanding the remarkable mathematical and statistical phenomena observed in deep learning, particularly feature learning and over-parameterization in deep learning. He is the editor-in-chief of SIAM Journal on Mathematics of Data Science (SIMODS).
Talk
The puzzle of dimensionality and feature learning in modern Deep Learning and LLM | June 3
Sessions in which Mikhail Belkin participates
Monday 3 June, 2024
Remarkable progress in AI has far surpassed expectations of just a few years ago is rapidly changing science and society. Never before had a technology been deployed so widely and so quickly with so little understanding of its fundamentals. Yet our understanding of the fundamental principles of AI is lacking. I will argue that developing a mathematical theory of deep learning is necessary for a successful AI transition and, furthermore, that such a theory may well be within reach. I will disc...