Maximum variance unfolding (MVU) is an effective heuristic for dimensionality reduction. It produces a low-dimensional representation of the data by maximizing the variance of the...
Le Song, Alex J. Smola, Karsten M. Borgwardt, Arth...
Rare category detection is an open challenge for active learning, especially in the de-novo case (no labeled examples), but of significant practical importance for data mining - ...
In this paper we investigate protocols for scheduling applications that consist of large numbers of identical, independent tasks on large-scale computing platforms. By imposing a ...
Barbara Kreaseck, Larry Carter, Henri Casanova, Je...
We consider a kernel-based approach to nonlinear classification that coordinates the generation of “synthetic” points (to be used in the kernel) with “chunking” (working wi...
Globally optimal formulations of geometric computer vision problems comprise an exciting topic in multiple view geometry. These approaches are unaffected by the quality of a provid...