TCS+ talk: Wednesday, October 14 — Jayadev Acharya, Cornell University
The next TCS+ talk will take place this coming Wednesday, October 14th at 1:00 PM Eastern Time (10:00 AM Pacific Time, 19:00 Central European Time, 17:00 UTC). Jayadev Acharya from Cornell University will speak about “Distributed Statistical Inference under Local Information Constraints ” (abstract below).
You can reserve a spot as an individual or a group to join us live by signing up on the online form. Due to security concerns, registration is required to attend the interactive talk. (The link to the YouTube livestream will also be posted on our website on the day of the talk, so people who did not sign up will still be able to watch the talk live.) As usual, for more information about the TCS+ online seminar series and the upcoming talks, or to suggest a possible topic or speaker, please see the website.
Abstract: We consider statistical inference tasks in a distributed setting where access to data samples is subjected to strict “local constraints,” through a unified framework that captures communication limitations and (local) privacy constraints as special cases. We study estimation (learning) and goodness-of-fit (testing) for both discrete and high-dimensional distributions. Our goal is to understand how the sample complexity increases under the information constraints.
In this talk we will provide an overview of this field and a sample of some of our results. We will discuss the role of (public) randomness and interactivity in information-constrained inference, and make a case for thinking about randomness and interactivity as resources.
The work is part of a long-term ongoing collaboration with Clément Canonne (IBM Research) and Himanshu Tyagi (IISc), and includes works done with Cody Freitag (Cornell), Yanjun Han (Stanford), Yuhan Liu (Cornell), and Ziteng Sun (Cornell).