In this paper, we explore small-variance asymptotics for exponential family Dirichlet process (DP) and hierarchical Dirichlet process (HDP) mixture models.

2.2 Dirichlet Process Mixture Models. The Dirichlet Process (DP) mixture model is a Bayesian nonparametric mixture model [12]; unlike most parametric mixture ...

for exponential family Dirichlet process (DP) and hierarchical Dirichlet process ... This paper explores such small-variance asymptotics ... 2.2 Dirichlet Process ...

In this paper, we explore small-variance asymptotics for exponential family Dirichlet process (DP) and hierarchical Dirichlet process (HDP) mixture models.

In this paper, we explore small-variance asymptotics for exponential family Dirichlet process (DP) and hierarchical Dirichlet process (HDP) mixture models.

Small-variance asymptotics for exponential family Dirichlet process mix- ture models. In NIPS. Kulis, B., and Jordan, M. 2012. Revisiting K-Means: New.

Dec 3, 2012 · For instance, in the context of clustering, such an approach yields connections between the k-means and EM algorithms. In this paper, we explore ...

This work proposes a new objective function derived from LDA by passing to the small-variance limit, and minimize the derived objective by using ideas from ...

Small-variance asymp- totics for exponential family Dirichlet process mixture models. In NIPS, 2012. H. W. Kuhn. The Hungarian method for the assignment.

Small-variance asymptotics for exponential family. Dirichlet process mixture models. In Advances in Neural Information Processing Systems, pages 3158–3166 ...