Nonparametric Bayesian Methods for Extracting Structure from Data
One desirable property of machine learning algorithms is the ability to balance the number of parameters in a model in accordance with the amount of available data. Incorporating nonparametric Bayesian priors into models is one approach of automatically adjusting model capacity to the amount...
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| Format: | Others |
| Language: | en_ca |
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2008
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| Online Access: | http://hdl.handle.net/1807/11235 |