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Bayesian Independent Component Analysis with prior constraints: An application in biosignal analysis

Abstract:: In many data-driven machine learning problems it is useful to consider the data as generated from a set of unknown (latent) generators or sources. The observations we make are then taken to be related to these sources through some unknown functionaility. Furthermore, the (unknown) number of underlying latent sources may be different to the number of observations and hence issues of model complexity plague the analysis. Recent developments in Independent Component Analysis (ICA) have shown tha...
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Publication status:: Published

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APA Style

Roberts, S., & Choudrey, R. (2005). Bayesian Independent Component Analysis with prior constraints: An application in biosignal analysis. DETERMINISTIC AND STATISTICAL METHODS IN MACHINE LEARNING, 3635, 159–179.

MLA Style

Roberts, S., and R. Choudrey. “Bayesian Independent Component Analysis with Prior Constraints: An Application in Biosignal Analysis.” DETERMINISTIC AND STATISTICAL METHODS IN MACHINE LEARNING, vol. 3635, 2005, pp. 159–79.

Chicago Style

Roberts, S, and R Choudrey. 2005. “Bayesian Independent Component Analysis with Prior Constraints: An Application in Biosignal Analysis.” DETERMINISTIC AND STATISTICAL METHODS IN MACHINE LEARNING 3635: 159–79.
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Publisher copy:: 10.1007/11559887_10

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+ Roberts, S More by this author

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+ Choudrey, R More by this author

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Bibliographic Details

Journal:: DETERMINISTIC AND STATISTICAL METHODS IN MACHINE LEARNING
Volume:: 3635
Pages:: 159-179
Publication date:: 2005-01-01
DOI:: 10.1007/11559887_10
EISSN:: 1611-3349
ISSN:: 0302-9743

Item Description

Language:: English
Keywords:: prior constraints

biosignal analysis

independent component analysis

variational Bayes
Pubs id:: pubs:318977
UUID:: uuid:8b3022f5-58f8-4589-9b3a-5f42985112da
Local pid:: pubs:318977
Source identifiers:: 318977
Deposit date:: 2013-11-17

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Copyright date:: 2005

Licence:: Terms and Conditions of Use for Oxford University Research Archive

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