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Seminar Jointly Organized by I2R, PREMIA and NTU |
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Sunday, 09 March 2008 |
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 We are pleased to invite you to the following seminar: Data Modeling Using Kernels and Information Theoretic Learning by Prof Jose C. Principe, Ph.D., Distinguished Professor of Electrical and Computer Engineering University of Florida, Gainesville. The seminar is jointly organized by Institute for Infocomm Research (I2R), Pattern Recognition and Machine Intelligence Association of Singapore (PREMIA) and Centre for Computational Intelligence (IDeAS Cluster), College of Engineering, Nanyang Technological University.
Title & Speaker
Data Modeling Using Kernels and Information Theoretic Learning
Prof Jose C. Principe, Ph.D.,
Distinguished Professor of Electrical and Computer Engineering
University of Florida, Gainesville
Date & Time
12 Mar 2008 ( Wednesday), 2.30 pm - 3.30pm
Venue
Lecture Theatre 3 (LT3), NS4-2-32
Nanyang Technological University
Abstract
This talk will introduce a new methodology to train linear or nonlinear
systems with entropy and divergence, as opposed to the well known mean
square error (MSE). The advantage is that more information about the
error signal is captured in the weights of the mapper. One of the corner
stones of information filtering is a methodology called information
theoretic learning (ITL) to estimate entropy directly from data, without
estimating the probability density function explicitly. Applications to
system identification (channel equalization), blind deconvolution and
matched filtering will be presented.
There is a very tight link between ITL and kernel methods being
developed now in the machine learning community. Time permitting, this
talk will present a new similarity function called correntropy. The name
was coined to show that it is similar to correlation but its mean value
across delays (or dimensions) is the argument of Renyi's quadratic
entropy. This similarity function has the potential to change the way we
design nonlinear signal processing algorithms.
BioData of Speaker
Jose C. Principe is Distinguished Professor of Electrical and Biomedical
Engineering at the University of Florida since 2002. He joined the
University of Florida in 1987, after an eight year appointment as
Professor at the University of Aveiro, in Portugal. Dr. Principe holds
degrees in electrical engineering from the University of Porto
(Bachelor), Portugal, University of Florida (Master and Ph.D.), USA and
a Laurea Honoris Causa degree from the Universita Mediterranea in Reggio
Calabria, Italy. Dr. Principe interests lie in nonlinear non-Gaussian
optimal signal processing and modeling and in biomedical engineering. He
created in 1991 the Computational NeuroEngineering Laboratory to
synergistically focus the research in biological information processing
models. He recently received the Gabor Award from the International
Neural Network Society for his contributions.
Dr. Principe is a Fellow of the IEEE, Fellow of the AIMBE, past
President of the International Neural Network Society, and Past Editor
in Chief of the Transactions of Biomedical Engineering, as well as a
former member of the Advisory Science Board of the FDA. He holds 5
patents and has submitted seven more. Dr. Principe was supervisory
committee chair of 50 Ph.D. and 61 Master students, and he is author of
more than 400 refereed publications (3 books, 4 edited books, 14 book
chapters, 116 journal papers and 276 conference proceedings).
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