A nonparametric Bayesian Poisson Gamma model for count data
Gupta, Sunil Kumar, Phung, Dinh and Venkatesh, Svetha 2012, A nonparametric Bayesian Poisson Gamma model for count data, in ICPR 2012 : Proceedings of 21st International Conference on Pattern Recognition, ICPR Organizing Committee, Tsubuka Science City, Japan, pp. 1815-1818.
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Title
A nonparametric Bayesian Poisson Gamma model for count data
We propose a nonparametric Bayesian, linear Poisson gamma model for count data and use it for dictionary learning. A key property of this model is that it captures the parts-based representation similar to nonnegative matrix factorization. We present an auxiliary variable Gibbs sampler, which turns the intractable inference into a tractable one. Combining this inference procedure with the slice sampler of Indian buffet process, we show that our model can learn the number of factors automatically. Using synthetic and real-world datasets, we show that the proposed model outperforms other state-of-the-art nonparametric factor models.
ISBN
9784990644109
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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