DSpace
 

Researchspace >
General science, engineering & technology >
General science, engineering & technology >
General science, engineering & technology >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/5570

Title: Learning structured representations of data
Authors: Barnard, E
Van der Walt, C
Davel, M
Van Heerden, C
Senekal, FP
Naidoo, T
Keywords: Data sets
Data analysis
Generality
Tractability
Bayesian networks
Issue Date: Nov-2009
Publisher: PRASA
Citation: Barnard, E, Van der Walt, C, Davel, M et al. Learning structured representations of data. 20th Annual Symposium of the Pattern Recognition Association of South Africa (PRASA), Stellenbosch, South Africa, 30 November-01 December 2009, pp 1-6
Abstract: Bayesian networks have shown themselves to be useful tools for the analysis and modelling of large data sets. However, their complete generality leads to computational and modelling complexities that have limited their applicability. We propose an approach to simplify and constrain Bayesian networks that strikes a more useful compromise between generality and tractability. These constrained graphical will allow us to build computationally tractable models for large high-dimensional data sets. We also describe examples of data sets drawn from image and speech processing on which can (1) further explore this constrained set of graphical models, and (2) analyse their performance as a general-purpose statistical data analysis tool.
Description: 20th Annual Symposium of the Pattern Recognition Association of South Africa (PRASA), Stellenbosch, South Africa, 30 November-01 December 2009
URI: http://www.prasa.org/proceedings/2009/prasa09-01.pdf
http://hdl.handle.net/10204/5570
ISBN: 978-0-7992-2356-9
Appears in Collections:Advanced mathematical modelling and simulation
Digital intelligence
Mobile intelligent autonomous systems
General science, engineering & technology

Files in This Item:

File Description SizeFormat
Barnard1_2009.pdf3.93 MBAdobe PDFView/Open
View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback