We study the information-theoretic limits of exactly recovering the support set of a sparse signal, using noisy projections defined by various classes of measurement matrices. Our ...
Wei Wang, Martin J. Wainwright, Kannan Ramchandran
Recent research into single–objective continuous Estimation– of–Distribution Algorithms (EDAs) has shown that when maximum–likelihood estimations are used for parametric d...
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Background: Constraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the gen...
Jacek Sroka, Lukasz Bieniasz-Krzywiec, Szymon Gwoz...
Abstract— Memetic algorithms arise as very effective algorithms to obtain reliable and high accurate solutions for complex continuous optimization problems. Nowadays, high dimens...