We address the problem of learning a kernel for a given supervised learning task. Our approach consists in searching within the convex hull of a prescribed set of basic kernels fo...
Andreas Argyriou, Raphael Hauser, Charles A. Micch...
We present an effective method to optimize over the parameters of an image patch descriptor to obtain one that is computationally more efficient while maintaining a high recogniti...
Decentralized partially observable Markov decision processes (Dec-POMDPs) constitute a generic and expressive framework for multiagent planning under uncertainty. However, plannin...
Frans A. Oliehoek, Shimon Whiteson, Matthijs T. J....
Segmenting arbitrary unions of linear subspaces is an important tool for computer vision tasks such as motion and image segmentation, SfM or object recognition. We segment subspac...
—Recently, opportunistic routing (OR) has been widely used to compensate for the low packet delivery ratio of multi-hop wireless networks. Previous works either provide heuristic...