The stability of low-rank matrix reconstruction is investigated in this paper. The -constrained minimal singular value ( -CMSV) of the measurement operator is shown to determine t...
The CUR decomposition provides an approximation of a matrix X that has low reconstruction error and that is sparse in the sense that the resulting approximation lies in the span o...
Training of conditional random fields often takes the form of a double-loop procedure with message-passing inference in the inner loop. This can be very expensive, as the need to...
—This paper considers the reconstruction of structured-sparse signals from noisy linear observations. In particular, the support of the signal coefficients is parameterized by h...
Abstract— We consider a wireless broadcast station that transmits packets to multiple users. The packet requests for each user may overlap, and some users may already have certai...