Language modeling is an effective and theoretically attractive probabilistic framework for text information retrieval. The basic idea of this approach is to estimate a language mo...
In this paper a graph-based method is presented which not only characterizes topological classification of the tessellated surfaces but also simultaneously generates the substanti...
We consider the problem of learning density mixture models for classification. Traditional learning of mixtures for density estimation focuses on models that correctly represent t...
Statistical approaches to language learning typically focus on either short-range syntactic dependencies or long-range semantic dependencies between words. We present a generative...
Thomas L. Griffiths, Mark Steyvers, David M. Blei,...
This work presents a novel approach in automatic detection of the lung nodules and is compared with respect to parametric nodule models in terms of sensitivity and specificity. A ...
Amal A. Farag, James Graham, Salwa Elshazly, Aly F...