It is not uncommon for modern systems to be composed of a variety of interacting services, running across multiple machines in such a way that most developers do not really unders...
We consider the problem of collectively approximating a set of sensor signals using the least amount of space so that any individual signal can be efficiently reconstructed within...
Generative model learning is one of the key problems in machine learning and computer vision. Currently the use of generative models is limited due to the difficulty in effective...
Background: With the rapid expansion of DNA sequencing databases, it is now feasible to identify relevant information from prior sequencing projects and completed genomes and appl...
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...