[talks] EE Seminar - Thursday, October 18, 2018, 4:30pm, E-Quad B205, Ayfer Ozgur Aydin, Stanford

[Emily Lawrence]

Department of Electrical Engineering

Seminar Series

 

Speaker: Prof. Ayfer Ozgur Aydin

                              Stanford University 

Title:        A Geometric Approach to two Problems in Networks: 

Learning High-Dimensional Distributions and Communication with Relays

Date:       Thursday, October 18, 2018          

Time:       4:30 pm   

Room:     Engineering Quadrangle B205 

Host:        Prof. Yuxin Chen

 

Abstract: We investigate the pivotal role geometry can play in
characterizing the fundamental limits of information flow in two different
network problems.  We first consider a classical problem in network
information theory: characterizing the capacity of a so-called relay
channel. Even though the relay channel has been one of the central problems
in network information theory, its capacity remains unknown for almost four
decades. We solve an open problem posed by Cover in 1987. This problem,
which Cover calls the "Capacity of the Relay Channel", corresponds to
characterizing the capacity of this channel at one special operating point.
Our approach is geometric and builds on an extension we develop for the
isoperimetric inequality on a high-dimensional sphere. We then turn to
another network problem, where the end goal is not to communicate a message
but learn a high-dimensional distribution or parameter from its distributed
samples under communication constraints. We first provide a geometric
characterization of Fisher information from quantized samples. We then use
this characterization to prove tight minimax bounds for distributed
estimation of common statistical models (such as the product Bernoulli
model, multinomial model, dense/sparse Gaussian location models). Our
results show that the impact of the communication constraint can be
drastically different depending on the tail behavior of the score function
of the model. Some of our results recover or strengthen existing results in
this area with simpler and more transparent proofs. We conclude with a
discussion on future directions in the intersection of geometry and
information theory.

 

First part of the talk is joint work with Xiugang Wu and Leighton Barnes.
Second part is joint work with Leighton Barnes, Yanjun Han and Tsachy
Weissman.

 

Bio:  Ayfer Ozgur received her Ph.D. degree in 2009 from the Information
Processing Group at EPFL, Switzerland. In 2010 and 2011, she was a
post-doctoral scholar at the same institution. She is an Assistant Professor
in the Electrical Engineering Department at Stanford University since 2012.
Her research interests include distributed communication and learning,
wireless systems, and information theory. Dr. Ozgur received the EPFL Best
Ph.D. Thesis Award in 2010, an NSF CAREER award in 2013, the Okawa
Foundation Research Grant and the  IEEE 2018 Communication Theory Technical
Committee (CTTC)  Early Achievement Award in 2018.

This seminar is supported with funds from the Korhammer Lecture Series.

 

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.cs.princeton.edu/pipermail/talks/attachments/20181011/e9552f1f/attachment.html>