Abstract--In this paper we address the task of accurately reconstructing a distributed signal through the collection of a small number of samples at a data gathering point using Co...
Riccardo Masiero, Giorgio Quer, Michele Rossi, Mic...
1 minimization can be used to recover sufficiently sparse unknown signals from compressed linear measurements. In fact, exact thresholds on the sparsity, as a function of the ratio...
Hyper-heuristics are identified as the methodologies that search the space generated by a finite set of low level heuristics for solving difficult problems. One of the iterative h...
The structural properties of graphs are usually characterized in terms of invariants, which are functions of graphs that do not depend on the labeling of the nodes. In this paper ...
Venkat Chandrasekaran, Pablo A. Parrilo, Alan S. W...
We present a novel probabilistic framework for rigid tracking and segmentation of shapes observed from multiple cameras. Most existing methods have focused on solving each of thes...