Bayesian Tensor Analysis

Vector data are normally used for probabilistic graphical models with Bayesian inference. However, tensor data, i.e., multidimensional arrays, are actually natural representations of a large amount of real data, in data mining, computer vision, and many other applications. Aiming at breaking the hug...

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Main Authors:	TAO, Dacheng, SUN, Jimeng, SHEN, Jialie, WU, Xindong, LI, Xuelong, Maybank, Stephen J., Faloutsos, Christos
Format:	text
Language:	English
Published:	Institutional Knowledge at Singapore Management University 2008
Subjects:	Computer Sciences
Online Access:	https://ink.library.smu.edu.sg/sis_research/411 http://dx.doi.org/10.1109/IJCNN.2008.4633981
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Institution:	Singapore Management University
Language:	English

id	sg-smu-ink.sis_research-1410
record_format	dspace
spelling	sg-smu-ink.sis_research-14102010-09-24T06:36:22Z Bayesian Tensor Analysis TAO, Dacheng SUN, Jimeng SHEN, Jialie WU, Xindong LI, Xuelong Maybank, Stephen J. Faloutsos, Christos Vector data are normally used for probabilistic graphical models with Bayesian inference. However, tensor data, i.e., multidimensional arrays, are actually natural representations of a large amount of real data, in data mining, computer vision, and many other applications. Aiming at breaking the huge gap between vectors and tensors in conventional statistical tasks, e.g., automatic model selection, this paper proposes a decoupled probabilistic algorithm, named Bayesian tensor analysis (BTA). BTA automatically selects a suitable model for tensor data, as demonstrated by empirical studies. 2008-05-01T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/411 info:doi/10.1109/IJCNN.2008.4633981 http://dx.doi.org/10.1109/IJCNN.2008.4633981 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Computer Sciences
institution	Singapore Management University
building	SMU Libraries
continent	Asia
country	Singapore Singapore
content_provider	SMU Libraries
collection	InK@SMU
language	English
topic	Computer Sciences
spellingShingle	Computer Sciences TAO, Dacheng SUN, Jimeng SHEN, Jialie WU, Xindong LI, Xuelong Maybank, Stephen J. Faloutsos, Christos Bayesian Tensor Analysis
description	Vector data are normally used for probabilistic graphical models with Bayesian inference. However, tensor data, i.e., multidimensional arrays, are actually natural representations of a large amount of real data, in data mining, computer vision, and many other applications. Aiming at breaking the huge gap between vectors and tensors in conventional statistical tasks, e.g., automatic model selection, this paper proposes a decoupled probabilistic algorithm, named Bayesian tensor analysis (BTA). BTA automatically selects a suitable model for tensor data, as demonstrated by empirical studies.
format	text
author	TAO, Dacheng SUN, Jimeng SHEN, Jialie WU, Xindong LI, Xuelong Maybank, Stephen J. Faloutsos, Christos
author_facet	TAO, Dacheng SUN, Jimeng SHEN, Jialie WU, Xindong LI, Xuelong Maybank, Stephen J. Faloutsos, Christos
author_sort	TAO, Dacheng
title	Bayesian Tensor Analysis
title_short	Bayesian Tensor Analysis
title_full	Bayesian Tensor Analysis
title_fullStr	Bayesian Tensor Analysis
title_full_unstemmed	Bayesian Tensor Analysis
title_sort	bayesian tensor analysis
publisher	Institutional Knowledge at Singapore Management University
publishDate	2008
url	https://ink.library.smu.edu.sg/sis_research/411 http://dx.doi.org/10.1109/IJCNN.2008.4633981
_version_	1770570414772191232

Bayesian Tensor Analysis

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