Elad Hazan, “Meta Optimization and Online Control”
Guest: Elad Hazan
Professor
Princeton University
Topic: “Meta Optimization and Online Control”
Abstract: In this talk we will discuss an emerging paradigm in differentiable reinforcement learning called “online nonstochastic control”. The new approach applies techniques from online convex optimization and convex relaxations to obtain new methods with provable guarantees for classical settings in optimal and robust control, nonlinear adaptive control and planning. We will then discuss a recent application of this framework to the setting of meta-optimization: the problem of how to choose the hyperparameters of a learning algorithm with provable guarantees.
Biography: Elad Hazan is a professor of computer science at Princeton University. His research focuses on the design and analysis of algorithms for basic problems in machine learning and optimization. Amongst his contributions are the co-invention of the AdaGrad algorithm for deep learning, and the first sublinear-time algorithms for convex optimization. He is the recipient of the Bell Labs prize, the IBM Goldberg best paper award twice, in 2012 and 2008, a European Research Council grant, a Marie Curie fellowship, twice the Google Research Award, and ACM fellowship. He served on the steering committee of the Association for Computational Learning and has been program chair for COLT 2015. In 2017 he co-founded In8 inc. focusing on efficient optimization and control, acquired by Google in 2018. He is the co-founder and director of Google AI Princeton.
In-person in Clark Hall, Room 110
OR
virtually over Zoom
Join Zoom Meeting:
https://wse.zoom.us/j/97055652302?pwd=dWFUUHRHS1lna2h5K0U1cEt4RDRrQT09
If you would like to meet with Elad Hazan before or after his seminar, please sign up for a time at this link: