(NOTE NEW DATE, 11/19) The Science of Modern Machine Learning: New Opportunities for Theory | Richard M. Karp Distinguished Lecture

NOTE NEW DATE: November 19

Deep learning, the technology underlying the recent progress in AI, has revealed some major surprises from the perspective of theory. These methods seem to achieve their outstanding performance through different mechanisms from those of classical learning theory, mathematical statistics, and optimization theory. Simple gradient methods find excellent solutions to nonconvex optimization problems, and without any explicit effort to control model complexity, they exhibit excellent prediction performance in practice. This talk will describe recent progress on the optimization and generalization properties of these methods, as well as some of the intriguing questions that they raise.

Peter Bartlett is professor of statistics and computer science at UC Berkeley and principal scientist at Google DeepMind. At Berkeley, he is the machine learning research director at the Simons Institute for the Theory of Computing, director of the Foundations of Data Science Institute, and director of the Collaboration on the Theoretical Foundations of Deep Learning. He is president of the Association for Computational Learning, honorary professor of mathematical sciences at the Australian National University, and coauthor with Martin Anthony of the book Neural Network Learning: Theoretical Foundations. He was awarded the Malcolm McIntosh Prize for Physical Scientist of the Year in Australia in 2001, and was chosen as an Institute of Mathematical Statistics Medallion Lecturer in 2008, an IMS fellow and Australian laureate fellow in 2011, a fellow of the ACM in 2018, and a recipient of the Chancellor's Distinguished Service Award in 2023. He was elected to the Australian Academy of Science in 2015.

The Richard M. Karp Distinguished Lectures were created in Fall 2019 to celebrate the role of Simons Institute Founding Director Dick Karp in establishing the field of theoretical computer science, formulating its central problems, and contributing stunning results in the areas of computational complexity and algorithms. Formerly known as the Simons Institute Open Lectures, the series features visionary leaders in the field of theoretical computer science and is geared toward a broad scientific audience.

Light refreshments will be available at 4 p.m., prior to the start of the lecture. 

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