Department of Mathematics
 Search | Help | Login | pdf version | printable version

Math @ Duke



Publications [#326753] of Robert Calderbank

Papers Published

  1. Wang, L; Renna, F; Yuan, X; Rodrigues, M; Calderbank, R; Carin, L, A general framework for reconstruction and classification from compressive measurements with side information, 2015 Ieee International Conference on Acoustics, Speech, and Signal Processing (Icassp), vol. 2016-May (May, 2016), pp. 4239-4243, ISBN 9781479999880 [doi]
    (last updated on 2018/12/09)

    © 2016 IEEE. We develop a general framework for compressive linear-projection measurements with side information. Side information is an additional signal correlated with the signal of interest. We investigate the impact of side information on classification and signal recovery from low-dimensional measurements. Motivated by real applications, two special cases of the general model are studied. In the first, a joint Gaussian mixture model is manifested on the signal and side information. The second example again employs a Gaussian mixture model for the signal, with side information drawn from a mixture in the exponential family. Theoretical results on recovery and classification accuracy are derived. The presence of side information is shown to yield improved performance, both theoretically and experimentally.
ph: 919.660.2800
fax: 919.660.2821

Mathematics Department
Duke University, Box 90320
Durham, NC 27708-0320