clustering of documents according to sharing of topics at multiple levels of abstraction. Given a corpus of documents, a posterior inference algorithm finds an approximation to a ...
David M. Blei, Thomas L. Griffiths, Michael I. Jor...
Prior distributions play a crucial role in Bayesian approaches to clustering. Two commonly-used prior distributions are the Dirichlet and Pitman-Yor processes. In this paper, we i...
Hanna M. Wallach, Shane Jensen, Lee Dicker, Kather...
A nonparametric Bayesian model for histogram clustering is proposed to automatically determine the number of segments when Markov Random Field constraints enforce smooth class assi...
We propose a novel nonparametric Bayesian model, Dual Hierarchical Dirichlet Processes (Dual-HDP), for trajectory analysis and semantic region modeling in surveillance settings, i...
Xiaogang Wang, Keng Teck Ma, Gee Wah Ng, W. Eric L...
Image segmentation algorithms partition the set of pixels of an image into a specific number of different, spatially homogeneous groups. We propose a nonparametric Bayesian model f...