Algorithms that enable the process of automatically mining distinct topics in document collections have become increasingly important due to their applications in many fields and ...
In this paper, we focus our attention on the problem of computing the ratio of two numbers, both of which are the summations of the private numbers distributed in different parties...
Collapsed Gibbs sampling is a frequently applied method to approximate intractable integrals in probabilistic generative models such as latent Dirichlet allocation. This sampling ...
This paper introduces LDA-G, a scalable Bayesian approach to finding latent group structures in large real-world graph data. Existing Bayesian approaches for group discovery (suc...
We present topic-regression multi-modal Latent Dirichlet Allocation (tr-mmLDA), a novel statistical topic model for the task of image and video annotation. At the heart of our new...