This paper reports on an approach which maps documents onto an ontology-based information space in order to provide support for machine-mediated communication. First, a composite ...
We present a technique for learning clothing models that enables the simultaneous animation of thousands of detailed garments in real-time. This surprisingly simple conditional mo...
Edilson de Aguiar, Leonid Sigal, Adrien Treuille, ...
Kernel methods have gained a great deal of popularity in the machine learning community as a method to learn indirectly in highdimensional feature spaces. Those interested in rela...
We present an algorithmic framework for learning multiple related tasks. Our framework exploits a form of prior knowledge that relates the output spaces of these tasks. We present...
In this paper we study the question of whether identifiable classes have subclasses which are identifiable under a more restrictive criterion. The chosen framework is inductive ...