Bridging CS and Math through the lens of Structure and Randomness
Speaker: Shachar Lovett, University of California, San Diego
Date: March 25, 2020, 2 p.m.
Host: Michael Overton
My research is focused on building bridges between different
areas within computer science, and between computer science and
mathematics. In particular, I am studying the role that structure and
randomness play in many computational problems. In this talk I will
focus a specific instantiation of the above paradigm. I will describe a
surprising connection between machine learning, complexity theory and
geometry. More concretely, I will describe how studying the power of
enriched queries in active learning led to a better understanding of the
3-SUM problem in complexity theory and point location problems in geometry.
Based on joint works with Daniel Kane, Shay Moran and Jiapeng Zhang.
Shachar Lovett is an Associate Professor in the Computer Science
department at the University of California, San Diego. He obtained his
PhD from the Weizmann Institute in 2010, has been a postdoc at the
Institute for Advanced Study between 2010 and 2012, and has been a
faculty member at the University of California, San Diego since. He is
interested in the role that structure and randomness play in computation
and mathematics, in particular in computational complexity,
optimization, machine learning and coding theory. He is a recipient of
an NSF Career award and a Sloan fellowship.
In-person attendance only available to those with active NYU ID cards.