Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
Abstract. We describe a simple CSP formalism for handling multi-attribute preference problems with hard constraints, one that combines hard constraints and preferences so the two a...
Eugene C. Freuder, Robert Heffernan, Richard J. Wa...
Generalizing the approach of a previous work [15] the authors present multilevel preconditioners for three-dimensional (3D) elliptic problems discretized by a family of Rannacher ...
Hough voting methods efficiently handle the high complexity of multiscale,
category-level object detection in cluttered scenes. The primary weakness
of this approach is however t...
Pradeep Yarlagadda, Antonio Monroy and Bjorn Ommer
In this paper, we investigate a problem of predicting what images are likely to appear on the Web at a future time point, given a query word and a database of historical image str...