In this paper we show that, surprisingly, it is possible to recover sparse signals from nonlinearly distorted measurements, even if the nonlinearity is unknown. Assuming just that...
Dense 3D reconstruction of extremely fast moving objects could contribute to various applications such as body structure analysis and accident avoidance and so on. The actual case...
This paper describes newly invented multiscale transforms known under the name of the ridgelet [6] and the curvelet transforms [9, 8]. These systems combine ideas of multiscale an...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
We describe a novel method for efficient reconstruction of phylogenetic trees, based on sequences of whole genomes or proteomes, whose lengths may greatly vary. The core of our me...
Igor Ulitsky, David Burstein, Tamir Tuller, Benny ...