ECE Fall Seminar Series
SPC Speaker, Xiugang Wu, University of Delaware
Title: Fundamental Limits in Information Networks: Communication, Inference and Learning
Abstract
Information networks surround us today in different forms and levels, ranging from neural networks, to social networks, to wireless networks and the Internet. The nodes in these networks accomplish tasks such as communication, inference and learning by exchanging information with each other. What are the fundamental laws that govern information flow in networks and how can a desired task be achieved most efficiently? This question was successfully answered by Shannon in 1948 for the case of a single point-point channel and when the desired task is the reliable communication of data, giving birth to the field of information theory.
In this talk, I will demonstrate how information theory, when enriched with new tools and ideas, can be used to characterize the fundamental limits on information flow in networks more complex than a point-point channel or for tasks other than communication. To this end, I will start by presenting our recent solution to a central problem in network communication that has been open for more than 30 years and named "The Capacity of the Relay Channel." I will then move on to establishing the fundamental limits of inference under rate constraints, and connect it to the information bottleneck method. Finally I will discuss a general principle for jointly designing the feature extractor and the inferrer based on a minimax approach to learning.
Bio
Xiugang Wu is an assistant professor at the University of Delaware, jointly appointed in Electrical and Computer Engineering, and Computer and Information Sciences. Previously, he was a postdoctoral fellow in Electrical Engineering at Stanford University, and received his Ph.D. degree in Electrical and Computer Engineering from the University of Waterloo. His research interests are in information theory, networks, data science, and the interplay between them. He is a recipient of the 2017 NSF Center for Science of Information (CSoI) Postdoctoral Fellowship
Monday, September 10, 2018 at 11:15am to 12:05pm
Evans Hall, Room 204
Evans Hall, University of Delaware, Newark, DE 19716, USA
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Students, Academics, Faculty & Staff, College of Engineering, Community, Lectures and Programs
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Free
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- ENGR - Electrical & Computer Engineering
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Amber Spivey
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302-831-2405
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