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Title:On Modeling Order and Structure With Applications to Computer Vision and Time Series Data
Author(s):Rajaram, Shyamsundar
Doctoral Committee Chair(s):Huang, Thomas S.
Department / Program:Electrical and Computer Engineering
Discipline:Electrical and Computer Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Engineering, Electronics and Electrical
Abstract:The final part of this dissertation is the development of a new category of graphical models called Poisson networks for modeling structured multivariate structured Poisson processes. Applications for Poisson networks arise in several scenarios, namely, modeling neural spike trains for learning structure of data transmission in the brain, arrival times at nodes for learning the structure of queuing networks, etc. We develop techniques for sampling, inference and structure learning of Poisson networks.
Issue Date:2007
Type:Text
Language:English
Description:128 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.
URI:http://hdl.handle.net/2142/81017
Other Identifier(s):(MiAaPQ)AAI3270006
Date Available in IDEALS:2015-09-25
Date Deposited:2007


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