In this paper, we propose a joint probabilistic topic model for simultaneously modeling the contents of multi-typed objects of a heterogeneous information network. The intuition b...
We address the problem of learning topic hierarchies from data. The model selection problem in this domain is daunting—which of the large collection of possible trees to use? We...
David M. Blei, Thomas L. Griffiths, Michael I. Jor...
Image annotation, the task of automatically generating description words for a picture, is a key component in various image search and retrieval applications. Creating image datab...
This paper presents a probabilistic model for sense disambiguation which chooses the best sense based on the conditional probability of sense paraphrases given a context. We use a...
This paper proposes a nonparametric Bayesian method for exploratory data analysis and feature construction in continuous time series. Our method focuses on understanding shared fe...