Abstract. This paper studies a Bayesian framework for density modeling with mixture of exponential family distributions. Variational Bayesian Dirichlet-Multinomial allocation (VBDM...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
In this paper, the task of text segmentation is approached from a topic modeling perspective. We investigate the use of latent Dirichlet allocation (LDA) topic model to segment a ...
Latent Dirichlet allocation is a fully generative statistical language model that has been proven to be successful in capturing both the content and the topics of a corpus of docum...
We develop latent Dirichlet allocation with WORDNET (LDAWN), an unsupervised probabilistic topic model that includes word sense as a hidden variable. We develop a probabilistic po...
Recently, the concept of a species containing both core and distributed genes, known as the supra- or pangenome theory, has been introduced. In this paper, we aim to develop a new ...