Shannon's sampling theory and its variants provide effective solutions to the problem of reconstructing a signal from its samples in some "shift-invariant" space, wh...
Sathish Ramani, Dimitri Van De Ville, Thierry Blu,...
The extension of Regular Expressions (REs) with an interleaving (shuffle) operator has been proposed in many occasions, since it would be crucial to deal with unordered data. Howe...
We present a simple and efficient method for reconstructing triangulated surfaces from massive oriented point sample datasets. The method combines streaming and parallelization, m...
In this paper, we introduce a simple but efficient greedy algorithm, called SINCO, for the Sparse INverse COvariance selection problem, which is equivalent to learning a sparse Ga...
We present a novel geometric model for robot mapping based on shape. Shape similarity measure and matching techniques originating from computer vision are specially redesigned for ...