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Centre for Pattern Recognition and Data Analytics
School of Information Technology
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GEELONG VIC 3220
S.K. Gupta, D. Phung, and S. Venkatesh. A nonparametric Bayesian Poisson gamma model for count data. In Proceedings of 21st International Conference on Pattern Recognition (ICPR), pages 1815-1818, 2012.
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.
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19th February 2015