We consider the problem of learning Gaussian multiresolution (MR) models in which data are only available at the finest scale and the coarser, hidden variables serve both to captu...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
The learning of probabilistic models with many hidden variables and nondecomposable dependencies is an important and challenging problem. In contrast to traditional approaches bas...
In this paper we are interested in the joint reconstruction of geometry and photometry of scenes with multiple moving objects from a collection of motion-blurred images. We make s...
Applications are subject to threat from a number of attack vectors, and limiting their attack surface is vital. By using privilege separation to constrain application access to pro...
Dhananjay Bapat, Kevin R. B. Butler, Patrick Drew ...
The performance of an ontology alignment technique largely depends on the amount of information that can be leveraged for the alignment task. On the Semantic Web, end-users may ex...