Correlated Compressive Sensing for Networked Data

  title={Correlated Compressive Sensing for Networked Data},
  author={Tianlin Shi and Da Tang and Liwen Xu and Thomas Moscibroda},
We consider the problem of recovering sparse correlated data on networks. To improve accuracy and reduce costs, it is strongly desirable to take the potentially useful side-information of network structure into consideration. In this paper we present a novel correlated compressive sensing method called CorrCS for networked data. By naturally extending Bayesian compressive sensing, we extract correlations from network topology and encode them into a graphical model as prior. Then we derive… CONTINUE READING