The Infinite Mixture of Infinite Gaussian Mixtures

Halid Z. Yerebakan, Bartek Rajwa, Murat Dundar

Neural Information Processing Systems 

Dirichlet process mixture of Gaussians (DPMG) has been used in the literature for clustering and density estimation problems. However, many real-world data exhibit cluster distributions that cannot be captured by a single Gaussian. Modeling such data sets by DPMG creates several extraneous clusters even when clusters are relatively well-defined.

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