[talks] TODAY November 12, 4:30pm, E-Quad B205 - Young-Han Kim, University of California, San Diego

[Emily Lawrence]

EE SEMINAR SERIES

 

Speaker: Young-Han Kim, University of California, San Diego

Title:      Data Science with Universal Probability

Day:       Monday, November 12, 2018

Time:     4:30 pm

Room:   B205 Engineering Quadrangle

Host:     Prof. Yuxin Chen

                

Abstract:

As Laplace famously asked "What is the probability that the sun will rise
tomorrow?," inferring the probabilities underlying a given data is at the
heart of many data science problems. In this talk, I will explore how to
assign probabilities to data such that its unknown distribution is uniformly
approximated without overfitting the data. I will develop the mathematical
foundation of this theory of universal probability which traces back to
Rissanen, to Ziv and Lempel, and even to Laplace, and present a general
framework for addressing many data science problems in a unified manner. To
illustrate this framework, I will present two practical applications in
nucleotide sequence classification and grayscale image denoising.

                

Bio:

Young-Han Kim received his B.S. degree in Electrical Engineering from Seoul
National University in 1996 and his Ph.D. degree in Electrical Engineering
(M.S. degrees in Statistics and in Electrical Engineering) from Stanford
University in 2006. Since then he has been on the faculty of the Department
of Electrical and Computer Engineering at the University of California, San
Diego, where he is currently a Professor. His research contributions have
been in information theory, communication engineering, and data science. He
has coauthored a highly cited textbook ``Network Information Theory''
(Cambridge University Press, 2011) and a recent monograph ``Fundamentals of
Index Coding'' (Now Publishers, 2018). He has received several awards and
honors for his contributions, including the NSF CAREER Award (2008), the
US-Israel BSF Bergmann Memorial Award (2009), the IEEE Information Theory
Paper Award (2012), and the first IEEE James L. Massey Research and Teaching
Award (2015). He is a fellow of the IEEE.

 

This seminar is supported with funds from the Korhammer Lecture Series

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