A slice sampler for restricted hierarchical beta process with applications to shared subspace learning
Gupta, Sunil Kumar, Phung, Dinh and Venkatesh, Svetha 2012, A slice sampler for restricted hierarchical beta process with applications to shared subspace learning, in UAI 2012 : Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence, AUAI Press, Corvallis, Or., pp. 316-325.
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Title
A slice sampler for restricted hierarchical beta process with applications to shared subspace learning
Conference on Uncertainty in Artificial Intelligence
Start page
316
End page
325
Total pages
10
Publisher
AUAI Press
Place of publication
Corvallis, Or.
Summary
Hierarchical beta process has found interesting applications in recent years. In this paper we present a modified hierarchical beta process prior with applications to hierarchical modeling of multiple data sources. The novel use of the prior over a hierarchical factor model allows factors to be shared across different sources. We derive a slice sampler for this model, enabling tractable inference even when the likelihood and the prior over parameters are non-conjugate. This allows the application of the model in much wider contexts without restrictions. We present two different data generative models – a linear Gaussian-Gaussian model for real valued data and a linear Poisson-gamma model for count data. Encouraging transfer learning results are shown for two real world applications – text modeling and content based image retrieval.
ISBN
9780974903989
Language
eng
Field of Research
080109 Pattern Recognition and Data Mining 080110 Simulation and Modelling
Socio Economic Objective
890205 Information Processing Services (incl. Data Entry and Capture)
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