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ESE Fall Colloquium Seminar – “Distributed Estimation Under Privacy and Communication Constraints”

October 19 at 11:00 AM - 12:00 PM

Distributed estimation is a central task in modern data science, where datasets are often generated from distributed sources or are too large to be stored on a centralized machine, and communication is subject to bandwidth and privacy limitations. In this talk, we will consider the problem of estimating high-dimensional distributions and their parameters from distributed samples under communication and differential privacy constraints. We will develop novel encoding and estimation mechanisms that simultaneously achieve optimal privacy and communication efficiency in various canonical settings, including both probabilistic and so called “distribution-free” models. We will investigate both global (worst-case) as well as local complexity of these tasks, where the latter captures the hardness of estimating a specific instance of the problem. We will complement our achievability results with information-theoretic lower bounds that describe how Fisher information from statistical samples scales with privacy and communication constraints. We will conclude by discussing how our theoretical results can be used to improve the experimental performance of federated learning algorithms.

Ayfer Ozgur

Associate Professor in the Electrical Engineering Department at Stanford University

Ayfer Ozgur is an Associate Professor in the Electrical Engineering Department at Stanford University where she is the Chambers Faculty Scholar in the School of Engineering. Her interests lie in information theory, wireless communication, statistics, and machine learning. Dr. Ozgur received the EPFL Best Ph.D. Thesis Award in 2010, the NSF CAREER award in 2013, the Okawa Foundation Research Grant, Faculty Research Awards from Google and Facebook, the IEEE Communication Theory Technical Committee (CTTC) Early Achievement Award in 2018 and was selected as the inaugural Goldsmith Lecturer of the IEEE ITSoc in 2020.

Details

Date:
October 19
Time:
11:00 AM - 12:00 PM
Website:
https://upenn.zoom.us/j/2822214402

Venue

Zoom – Meeting ID: 282 221 4402

Organizer

Electrical and Systems Engineering
Phone:
215-898-6823
Email:
eseevents@seas.upenn.edu
Website:
http://www.ese.upenn.edu/