Statistical topic models provide a general data-driven framework for automated discovery of high-level knowledge from large collections of text documents. While topic models can p...
Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyv...
In this paper, we study semistructured data and indexes preserving inclusion constraints. A semistructured datum is modelled by multi-rooted edge-labeled directed graphs. We consi...
The paper presents a complete framework for spatial indexing support in a distributed setting. We consider a shared-nothing environment where a set of servers provides independent...
We present a method for learning complex appearance mappings, such as occur with images of articulated objects. Traditional interpolation networks fail on this case since appearan...
We will describe three kinds of probabilistic induction problems, and give general solutions for each , with associated convergence theorems that show they tend to give good proba...