Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
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...
The next wave in search technology will be driven by the identification, extraction, and exploitation of real-world entities represented in unstructured textual sources. Search sy...
Managing large-scale software projects involves a number of activities such as viewpoint extraction, feature detection, and requirements management, all of which require a human a...
A human annotator can provide hints to a machine learner by highlighting contextual "rationales" for each of his or her annotations (Zaidan et al., 2007). How can one ex...