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UBC Theses and Dissertations
On-line EM and quasi-Baye or : how I learned to stop worrying and love stochastic approximation Bao, Kejie
Abstract
The EM algorithm is one of the most popular statistical learning algorithms. Unfortunately, it is a batch learning method. For large data sets and real-time systems, we need to develop on-line methods. In this thesis, we present a comprehensive study of on-line EM algorithms. We use Bayesian theory to propose a new on-line EM algorithm for multinomial mixtures. Based on this theory, we show that there is a direct connection between the setting of Bayes priors and the so-called learning rates of stochastic approximation algorithms, such as on-line EM and quasi-Bayes . Finally, we present extensive simulations, comparisons and parameter sensitivity studies on both synthetic data and documents with text, images and music.
Item Metadata
| Title |
On-line EM and quasi-Baye or : how I learned to stop worrying and love stochastic approximation
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| Creator | |
| Publisher |
University of British Columbia
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| Date Issued |
2003
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| Description |
The EM algorithm is one of the most popular statistical learning algorithms. Unfortunately, it is a batch learning method. For large data sets and real-time systems, we need to develop on-line methods. In this thesis, we present a comprehensive study of on-line EM algorithms. We use Bayesian theory to propose a new on-line EM algorithm for multinomial mixtures. Based on this theory, we show that there is a direct connection between the setting of Bayes priors and the so-called learning rates of stochastic approximation algorithms, such as on-line EM and quasi-Bayes . Finally, we present extensive simulations, comparisons and parameter sensitivity studies on both synthetic data and documents with text, images and music.
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| Extent |
2222843 bytes
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| Genre | |
| Type | |
| File Format |
application/pdf
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| Language |
eng
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| Date Available |
2009-11-02
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| Provider |
Vancouver : University of British Columbia Library
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| Rights |
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.
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| DOI |
10.14288/1.0051701
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| URI | |
| Degree (Theses) | |
| Program (Theses) | |
| Affiliation | |
| Degree Grantor |
University of British Columbia
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| Graduation Date |
2003-11
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| Campus | |
| Scholarly Level |
Graduate
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| Aggregated Source Repository |
DSpace
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Rights
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.