Talks & Seminars
Title: Optimization for Derandomization: Polynomial Identity Testing, Geodesically Convex Optimization and more
Dr. Ankit Garg, Microsoft Research New England
Date & Time: January 9, 2018 11:30
Venue: CC 109 Room, 01st Floor, New CSE Bldg.
Randomness plays an important role across scientific disciplines. In theoretical computer science, there is a large body of work trying to understand the role of randomness in computation. An important part in this quest is the polynomial identity testing question which asks if one can test identities deterministically. In this talk, I will talk about deterministic identity testing of a special class of polynomials using tools from optimization such as alternating minimization and second order methods. The class of problems that we solve form an amazing web of connections across areas such as geodesically convex optimization, quantum information theory, representation theory, non-commutative algebra and functional analysis. I will also outline applications to these areas. The talk will be based on several joint works with Zeyuan Allen-Zhu, Peter Burgisser, Leonid Gurvits, Yuanzhi Li, Rafael Oliveira, Michael Walter and Avi Wigderson.
Speaker Profile:
Ankit Garg is a postdoctoral researcher at Microsoft Research New England. He obtained his PhD in Computer Science from Princeton University under the supervision of Mark Braverman. Before that, he got his undergraduate degree in Computer Science from the Indian Institute of Technology, Delhi. His research interests lie in theoretical computer science and complexity theory, particularly in algebraic complexity, communication complexity and optimization.
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