Publications

A Fast Stochastic Plug-and-Play ADMM for Imaging Inverse problems

  • Junqi Tang, Mike Davies. 2020
  • [Preprint]

CNN Denoisers as Non-Local Filters: The Neural Tangent Denoiser

  • Julian Tachella, Junqi Tang, Mike Davies, 2020
  • [Preprint]

SPRING: A Fast Stochastic Proximal Alternating Method for Non-smooth Non-convex Optimization

  • Derek Driggs*, Junqi Tang*, Jingwei Liang, Mike Davies, Carola-Bibiane Schönlieb, 2020
  • [Preprint]

The Practicality of Stochastic Optimization in Imaging Inverse Problems

  • Junqi Tang, Karen Egiazarian,  Mohammad Golbabaee, Mike Davies
  • IEEE Transactions on Computational Imaging, 2020
  • [Download PDF]

The Limitation and Practical Acceleration of Stochastic Gradient Algorithms in Inverse Problems

  • Junqi Tang, Karen Egiazarian,  Mike Davies.
  • International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019
  • [Download PDF]

Structure-Adaptive Accelerated Coordinate Descent

  • Junqi Tang, Mohammad Golbabaee, Francis Bach,  Mike Davies.
  • Submitted, 2018
  • [Download PDF]

Rest-Katyusha: Exploiting the Solution’s Structure via Scheduled Restart Schemes

  • Junqi Tang, Mohammad Golbabaee, Francis Bach,  Mike Davies.
  • Advances in Neural Information Processing Systems, 2018.
  • [Download PDF] [Poster]

Gradient Projection Iterative Sketch for Large-Scale Constrained Least-Squares

Exploiting the Structure via Sketched Gradient Algorithms

  • Junqi Tang, Mohammad Golbabaee, Mike Davies.
  • IEEE conference on Signal and Information Processing (GlobalSIP),  2017.
  • [Download PDF] [bibtex]