3 accepted papers
Neural networks have been shown to be vulnerable against minor adversarial perturbations of their inputs, especially for high dimensional data under $\ell_\infty$ attacks.To combat this problem, techniques like adversarial training have been employed to obtain models that are robust on the training…
We consider the reconstruction of group-sparse vectors from sign measurements of random projections. In particular, we establish conditions on the number of measurements under which such signal ensembles can be recovered up to a prescribed accuracy. The results rely on a mixed restricted isometry pr…
The mutual coherence provides a basis for deriving recovery guarantees in compressed sensing. In this paper, the mutual coherence of spherical harmonics sensing matrices is examined for a class of sensing patterns common in practice and is used as a figure of merit for designing sensing matrices. We…