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231224s2015 xx |||||o 00| ||eng c |
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|a 10.1109/TPAMI.2014.2318721
|2 doi
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|a DE-627
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|e rakwb
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|a eng
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| 100 |
1 |
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|a Broderick, Tamara
|e verfasserin
|4 aut
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| 245 |
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|a Combinatorial Clustering and the Beta Negative Binomial Process
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|c 2015
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
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|2 rdamedia
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|a ƒa Online-Ressource
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|2 rdacarrier
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|a Date Completed 27.05.2016
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|a Date Revised 10.09.2015
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|a published: Print
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|a Citation Status MEDLINE
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|a We develop a Bayesian nonparametric approach to a general family of latent class problems in which individuals can belong simultaneously to multiple classes and where each class can be exhibited multiple times by an individual. We introduce a combinatorial stochastic process known as the negative binomial process ( NBP ) as an infinite-dimensional prior appropriate for such problems. We show that the NBP is conjugate to the beta process, and we characterize the posterior distribution under the beta-negative binomial process ( BNBP) and hierarchical models based on the BNBP (the HBNBP). We study the asymptotic properties of the BNBP and develop a three-parameter extension of the BNBP that exhibits power-law behavior. We derive MCMC algorithms for posterior inference under the HBNBP , and we present experiments using these algorithms in the domains of image segmentation, object recognition, and document analysis
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|a Journal Article
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|a Research Support, U.S. Gov't, Non-P.H.S.
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| 700 |
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|a Mackey, Lester
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Paisley, John
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Jordan, Michael I
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 37(2015), 2 vom: 01. Feb., Seite 290-306
|w (DE-627)NLM098212257
|x 1939-3539
|7 nnns
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| 773 |
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|g volume:37
|g year:2015
|g number:2
|g day:01
|g month:02
|g pages:290-306
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|u http://dx.doi.org/10.1109/TPAMI.2014.2318721
|3 Volltext
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|d 37
|j 2015
|e 2
|b 01
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|h 290-306
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