In this paper, we present a variational Bayes (VB) approach for image segmentation. First, image is modeled by a mixture model, and then with the techniques of factor analyzer, th...
Zhenglong Li, Qingshan Liu, Jian Cheng, Hanqing Lu
Topic modeling techniques have widespread use in text data mining applications. Some applications use batch models, which perform clustering on the document collection in aggregat...
We propose a novel bilingual topical admixture (BiTAM) formalism for word alignment in statistical machine translation. Under this formalism, the parallel sentence-pairs within a ...
We develop the syntactic topic model (STM), a nonparametric Bayesian model of parsed documents. The STM generates words that are both thematically and syntactically constrained, w...
Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...