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...
This paper describes nonparametric Bayesian treatments for analyzing records containing occurrences of items. The introduced model retains the strength of previous approaches that...
A nonparametric Bayesian approach to co-clustering ensembles is presented. Similar to clustering ensembles, coclustering ensembles combine various base co-clustering results to ob...
Pu Wang, Kathryn B. Laskey, Carlotta Domeniconi, M...
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...
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...