Set-valued estimation offers a way to account for imprecise knowledge of the prior distribution of a Bayesian statistical inference problem. The set-valued Kalman filter, which p...
This paper presents a calibration-free line-based tracking method to augment virtual objects into a video sequence. The presented method uses a cube on the first image to calibrat...
Sparse methods for supervised learning aim at finding good linear predictors from as few variables as possible, i.e., with small cardinality of their supports. This combinatorial ...
We investigate the recovery of signals exhibiting a sparse representation in a general (i.e., possibly redundant or incomplete) dictionary that are corrupted by additive noise adm...
Christoph Studer, Patrick Kuppinger, Graeme Pope, ...
In this paper we present a framework for logic programming agents to take part in games in such a way that stable models of the system, the ones agreed upon by all the members, co...