Plug-In Stochastic Gradient Method
arXiv:1811.03659
Abstract
Plug-and-play priors (PnP) is a popular framework for regularized signal reconstruction by using advanced denoisers within an iterative algorithm. In this paper, we discuss our recent online variant of PnP that uses only a subset of measurements at every iteration, which makes it scalable to very large datasets. We additionally present novel convergence results for both batch and online PnP algorithms.
To be presented at International Biomedical and Astronomical Signal Processing (BASP) Frontiers workshop 2019