Automatic metadata generation may provide a solution to the problem of inconsistent, unreliable metadata describing resources on the Web. The Resource Description Framework (RDF [...
Charlotte Jenkins, Mike Jackson, Peter Burden, Jon...
Discovering rare categories and classifying new instances of them is
an important data mining issue in many fields, but fully supervised
learning of a rare class classifier is pr...
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher ...
The proliferation of text documents on the web as well as within institutions necessitates their convenient organization to enable efficient retrieval of information. Although tex...
Sriharsha Veeramachaneni, Diego Sona, Paolo Avesan...
We propose the framework of mutual information kernels for learning covariance kernels, as used in Support Vector machines and Gaussian process classifiers, from unlabeled task da...