We address the problem of computing joint sparse representation of visual signal across multiple kernel-based representations. Such a problem arises naturally in supervised visual...
We propose a family of kernels between images, defined as kernels between their respective segmentation graphs. The kernels are based on soft matching of subtree-patterns of the r...
In this paper we are concerned with reproducing kernel Hilbert spaces HK of functions from an input space into a Hilbert space Y, an environment appropriate for multi-task learnin...
Andrea Caponnetto, Charles A. Micchelli, Massimili...
In this paper, we consider a smoothing kernelbased classification rule and propose an algorithm for optimizing the performance of the rule by learning the bandwidth of the smoothi...
Bharath K. Sriperumbudur, Omer A. Lang, Gert R. G....
Recent work has introduced Boolean kernels with which one can learn linear threshold functions over a feature space containing all conjunctions of length up to k (for any 1 ≤ k ...