English

Plug-In Stochastic Gradient Method

Signal Processing 2018-11-12 v1 Machine Learning
Authors: Yu Sun , Brendt Wohlberg , Ulugbek S. Kamilov
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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.

Keywords

plug-and-play image reconstruction

Cite

@article{arxiv.1811.03659,
  title  = {Plug-In Stochastic Gradient Method},
  author = {Yu Sun and Brendt Wohlberg and Ulugbek S. Kamilov},
  journal= {arXiv preprint arXiv:1811.03659},
  year   = {2018}
}

Comments

To be presented at International Biomedical and Astronomical Signal Processing (BASP) Frontiers workshop 2019

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