简介: |
Abstract
In this talk I will describe the proofs of some "invariance principles" in probability; the Central Limit Theorem, the Berry--Esseen Theorem, and multidimensional and higher-degree versions thereof. I will discuss these proofs from a computer science perspective, and mention some recent applications to fields such as property testing, derandomization, learning, and inapproximability.
Bio of the Speaker
Ryan O'Donnell received a B. Sc. from the University of Toronto in 1999 and a Ph.D. from the MIT Mathematics Department in 2003. His Ph.D. advisor was Madhu Sudan. Following this he was a postdoc at IAS for a year in Avi Wigderson’s group, and a postdoc at Microsoft Research for two years in Jennifer Chayes’s group. Since 2006 he has been an assistant professor in the Computer Science Department at Carnegie Mellon University. He is the recipient of the 2002 CCC Best Student Paper Award, the 2003 CCC Best Paper Award, an NSF CAREER grant, the Okawa Grant, the Sloan Fellowship, the BSF Pazy Memorial award, and the von Neumann Fellowship from the Institute for Advanced Study. Ryan’s research interests include Analysis of Boolean Functions, Hardness of Approximation, Learning Theory, and Probability. |
