A unifying representation for a class of dependent random measures

11/20/2012
by   Nicholas J. Foti, et al.
0

We present a general construction for dependent random measures based on thinning Poisson processes on an augmented space. The framework is not restricted to dependent versions of a specific nonparametric model, but can be applied to all models that can be represented using completely random measures. Several existing dependent random measures can be seen as specific cases of this framework. Interesting properties of the resulting measures are derived and the efficacy of the framework is demonstrated by constructing a covariate-dependent latent feature model and topic model that obtain superior predictive performance.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset