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[theory-seminar] "The online convex optimization approach to control" – Elad Hazan (Thu, 5-May @ 4:00pm)

Tavor Baharav tavorb at
Mon May 2 11:49:38 PDT 2022

The online convex optimization approach to controlElad Hazan – Professor,

Thu, 5-May / 4:00pm / Packard 101 (in person)

*Please join us for coffee and snacks at 3:30pm in the Grove outside
Packard (near Bytes' outdoor seating). The talk will be streamed on Zoom
for those unable to attend in

In this talk we will discuss an emerging paradigm in differentiable
reinforcement learning called “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. We will discuss recent extensions to nonlinear
adaptive control and planning.

No background is required for this talk, and relevant materials can be
found here <>.

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. He is the co-founder and director of
Google AI Princeton.

*This talk is hosted by the ISL Colloquium
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to the mailing list isl-colloq at

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