SILO



The weekly SILO Seminar Series is made possible through the generous support of the 3M Company and its Advanced Technology Group

3M

with additional support from the Analytics Group of the Northwestern Mutual Life Insurance Company

Northwestern Mutual

Enhanced Face Recognition using Message-Passing Algorithm | On How Searching is the New Packing

Ke Shen | Yana Shkel, Undergrad in Math and graduate student in ECE respectively

Date and Time: May 09, 2012 (12:30 PM)
Location: Orchard room (3280) at the Wisconsin Institute for Discovery Building

Abstract:

**** Ke Shen:

Title: Enhanced Face Recognition using Message-Passing Algorithm

Abstract: The goal of this project is to develop theories and algorithms to facilitate large-scale, unconstrained identity discovery, using images containing faces where the individuals belong to various social networks. By exploiting the contextual information from multiple photos and other resources, a delicate social and affiliation network structure can be exposed, allowing us to leverage such information and enhance the accuracy of face recognition.

This talk will introduce some background on affiliation networks, related problems in face recognition, and how affiliation networks relate to face recognition. Then we present an explicit real-world example, followed by message-passing algorithms we developed based on an analogy with the theory of Tanner graphs in coding theory and iterative decoding through belief propagation. We conclude with some challenges we face as regards such message-passing algorithms.

**** Yana
Title: On How Searching is the New Packing

Abstract: In this talk I will set up
the problem of communicating over Multiple Access Channels with
feedback. I will begin by introducing the channel coding problem and
the classical packing-type solutions to this problem using Binary
Symmetric and Additive White Gaussian Noise Channels as examples. I
will then contrast how coding over these channels in the presence of
feedback can also be interpreted as a search problem using recently
discovered Posterior Matching principle. Finally, I will introduce
the challenges and potential directions for characterizing capacity
region of an arbitrary Multiple Access Channel with feedback using
ideas of Posterior Matching.