Events Calendar

CS Distinguished Lecture: Ronitt Rubinfeld (MIT and Tel Aviv University) - Testing Properties of Distributions Over Big Domains

Speaker: Ronitt Rubinfeld, MIT and Tel Aviv University

Talk Title: Testing Properties of Distributions Over Big Domains

Series: Computer Science Distinguished Lecture Series

Abstract: We describe an emerging research direction regarding the complexity of testing global properties of discrete distributions, when given access to only a few samples from the distribution. Such properties might include testing if two distributions have small statistical distance, testing various independence properties, testing whether a distribution has a specific shape (such as monotone decreasing, k-modal, k-histogram, monotone hazard rate,...), and approximating the entropy. We describe bounds for such testing problems whose sample complexities are sublinear in the size of the support.

This lecture satisfies requirements for CSCI 591: Research Colloquium.


Biography: Ronitt Rubinfeld is a professor in the Department of Electrical Engineering and Computer Science and a member of the Computer Science and Artificial Intelligence Laboratory. Ronitt's main research area is theory of computation. Ronitt received her PhD from the University of California, Berkeley in 1991, and prior to that graduated from the University of Michigan with a BSE in Electrical and Computer Engineering. Before coming to MIT, Ronitt held postdoctoral researcher positions at Princeton University and Hebrew University. In 1992, she joined the faculty of the Computer Science Department at Cornell University, where she was an ONR Young Investigator, a Sloan Research Fellow, the 1995 Cornell Association for Computer Science Undergraduates Faculty of the Year, and a recipient of the Cornell College of Engineering Teaching Award. From 1999 to 2003, Ronitt was a Senior Research Scientist at NEC Research Laboratories, and in 2004, she was a Fellow at the Radcliffe Institute for Advanced Study.

Ronitt's research interests include randomized and sublinear time algorithms. In particular, her work focuses on what can be understood about data by looking at only a very small portion of it.



Host: Computer Science Department

Location: Henry Salvatori Computer Science Center (SAL) - 101

Audiences: Everyone Is Invited

Contact: Computer Science Department