16 citations
2 papers
cs.LG2019★ 16 cited
Robust learning with implicit residual networks
Viktor Reshniak, Clayton Webster
In this effort, we propose a new deep architecture utilizing residual blocks inspired by implicit discretization schemes. As opposed to the standard feed-forward networks, the outp…
math.OC2017★ 3 cited
On the strong convergence of forward-backward splitting in reconstructing jointly sparse signals
Nick Dexter, Hoang Tran, Clayton Webster
We consider the problem of reconstructing an infinite set of sparse, finite-dimensional vectors, that share a common sparsity pattern, from incomplete measurements. This is in cont…