A new dictionary selection approach for sparse coding, called parametric dictionary design, has recently been introduced. The aim is to choose a dictionary from a class of admissi...
Mehrdad Yaghoobi, Laurent Daudet, Michael E. Davie...
In this paper, motivated by network inference and tomography applications, we study the problem of compressive sensing for sparse signal vectors over graphs. In particular, we are ...
—In compressive sensing (CS), the Restricted Isometry Property (RIP) is a powerful condition on measurement operators which ensures robust recovery of sparse vectors is possible ...
Han Lun Yap, Armin Eftekhari, Michael B. Wakin, Ch...
In this paper, we present a general theory of adaptive mathematical morphology (AMM) in the Euclidean space. The proposed theory preserves the notion of a structuring element, whi...
We address the problem of loading transactional datasets into main memory and estimating the density of such datasets. We propose BoolLoader, an algorithm dedicated to these tasks;...