17 citations · 21 across the 3 of their papers we have counts for
4 papers
Maximal Sparsity with Deep Networks?
Bo Xin, Yizhou Wang, Wen Gao +1
The iterations of many sparse estimation algorithms are comprised of a fixed linear filter cascaded with a thresholding nonlinearity, which collectively resemble a typical neural n…
Image Super-Resolution via Sparse Bayesian Modeling of Natural Images
Haichao Zhang, David Wipf, Yanning Zhang
Image super-resolution (SR) is one of the long-standing and active topics in image processing community. A large body of works for image super resolution formulate the problem with…
Non-Convex Rank Minimization via an Empirical Bayesian Approach
David Wipf
In many applications that require matrix solutions of minimal rank, the underlying cost function is non-convex leading to an intractable, NP-hard optimization problem. Consequently…
Dual-Space Analysis of the Sparse Linear Model
David Wipf, Yi Wu
Sparse linear (or generalized linear) models combine a standard likelihood function with a sparse prior on the unknown coefficients. These priors can conveniently be expressed as a…