Linear and kernel discriminant analyses are popular approaches for supervised dimensionality reduction. Uncorrelated and regularized discriminant analyses have been proposed to ove...
The theory of compressed sensing has a natural application in interferometric aperture synthesis. As in many real-world applications, however, the assumption of random sampling, w...
Stephan Wenger, Soheil Darabi, Pradeep Sen, Karl-H...
We study the problem of answering queries posed on virtual views of XML documents, a problem commonly encountered when enforcing XML access control and integrating data. We approa...
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
While many interesting dynamic load balancing schemes have been proposed for efficient use of limited bandwidth and to increase the capacity of congested or hot spots (or cells) in...