21st Canadian Conference on Electrical and Computer Engineering
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Welcome
to the 21th annual
IEEE Canada Conference

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The Wonders of Technology May 4-7, 2008
Sheraton Fallsview
Niagara Falls
Ontario, Canada

Tutorial C: Message-passing algorithms for solving problems in telecommunications, signal processing, and biomedicine



Sunday Morning, May 4
9 a.m. - 12 p.m.
Oneida Room


Presented by

Prof. Brendan Frey - Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada

Abstract

Many problems in science and engineering can be formulated as determining the values of a set of unknown variables, given a noisy set of observations and uncertain knowledge about how all the variables and observations are related. For example, how would you determine a transmitted message, based on a noisy received signal? How would you determine the pattern of blood flow in a patient's heart, based on a corrupted MRI image? How would you identify a small number of face images that summarize a diverse set of face images? How would you identify a small number of sentences that accurately reflect the content of a document? How would you learn a codebook useful for quantizing speech signals? How would you identify a small number of cities that are most easily accessible from all other cities by commercial airline? How would you identify segments of DNA that reflect the expression properties of genes? In this tutorial, I will review message-passing algorithms that have recently gained a lot of interest in the engineering, computer science and computational biology communities. These algorithms work by exchanging messages between variables and observations -- these messages try to pin down probable solutions while taking into account uncertainties. As an example, I will describe how this approach can be used to derive an algorithm that my colleagues and I recently introduced, called `affinity propagation'. This algorithm solves the problem of summarizing a set of observations by a subset of exemplars, which can then be used for decision-making or coding. I'll discuss aspects of message-passing and affinity propagation in particular that could impact efficient implementation in multi-core architectures, FPGA hardware and VLSI hardware.



Presenter's Biography

Brendan Frey is a Professor in Electrical and Computer Engineering at the University of Toronto and is cross-appointed to Computer Science and the Centre for Cellular and Biomolecular Research. Dr. Frey studies machine learning algorithms, probabilistic graphical models, molecular biology and computer vision. His most highly-cited work is on 'factor graphs and the sum-product algorithm'. In 2005, Dr. Frey's work on computational 'epitomes' with applications in vision received honorable mention for Best Paper at the IEEE Conference on Computer Vision and Pattern Recognition. Dr. Frey's 2005 Nature Genetics paper reporting the first-ever exon-resolution analysis of the mammalian genome stirred up controversy in the molecular biology and genomics communities, which was reconciled in his favour in the March 2006 issue of Science. Dr. Frey's most recent work is on a machine learning algorithm called affinity propagation, which was described in the Feburary 16, 2007 issue of Science. Dr. Frey is a Fellow of the Canadian Institute for Advanced Research. In May 2007, he was named as one of Canada's Top 40 Under 40 -- one of the top 40 leaders of today and tomorrow in Canada, under the age of 40. Dr. Frey holds the Canada Research Chair in Information Processing and Machine Learning and is a winner of the Premier's Research Excellence Award, a former Fellow of the Beckman Foundation and a recipient of the NSERC 1967 Science and Engineering Award.

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