Many data are naturally modeled by an unobserved hierarchical structure. In this paper we propose a flexible nonparametric prior over unknown data hierarchies.
Jun 5, 2010 · In this paper we propose a flexible nonparametric prior over unknown data hierarchies. The approach uses nested stick-breaking processes to ...
In this paper we propose a flexible nonparametric prior over unknown data hierarchies. The approach uses nested stick-breaking processes to allow for trees of ...
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Our construction provides an intuitive and flexible model for hierarchical data, while maintaining tractability for inference. The Dirichlet process (DP) is a ...
This paper uses nested stick-breaking processes to allow for trees of unbounded width and depth, where data can live at any node and are infinitely ...
PDF | Many data are naturally modeled by an unobserved hierarchical structure. In this paper we propose a flexible nonparametric prior over unknown data.
We present a Bayesian nonparametric prior called the hierarchical tree-structured stick-breaking prior, which is a natural extension to the tree-structured ...
The generation method produces hierarchical data that follows the three critical OCH requirements. The Retention requirement is satisfied because the generator ...
Dec 6, 2010 · In this paper we propose a flexible nonparametric prior over unknown data hierarchies. The approach uses nested stick-breaking processes to ...
Nov 24, 2010 · It's a nonparametric prior over unknown data hierarchies. The nested stick-breaking processes allow for trees of unbounded width and depth.