Dr Jingwei Liang

Career

  • 2017-date: Postdoc Research Associate, DAMTP, University of Cambridge
  • 2013-2016: PhD in Applied Mathematics, ENSICAEN, France
  • 2010-2013: Master in Applied Mathematics, Shanghai Jiao Tong University, China

Research

Jingwei Liang is a postdoc research associate of the Cambridge Image Analysis group of Dr Carola-Bibiane Schönlieb. With his work on convergence rate of first-order operator splitting methods he obtained his doctoral degree at ENSICAEN, France, under supervision of Prof. Jalal M. Fadili (ENSICAEN) and Prof. Gabriel Peyré (ENS, Paris). His current research focuses on non-smooth optimization, image processing and machine learning.

Selected Publications

Journal publications

  • JL, J. Fadili and G, Peyré, Activity Identification and Local Linear Convergence of Forward–Backward- type Methods, SIAM Journal on Optimization, 27 (1), 408-437, 2017.
  • JL, J. Fadili and G. Peyré, Local Convergence Properties of Douglas–Rachford and Alternating Direction Method of Multipliers, Journal of Optimization Theory and Applications, 72 (3), 874- 913, 2017.
  • JL, J. Fadili and G. Peyré, Convergence Rates with Inexact Non-expansive Operators, Mathematical Programming ser. A, 159 (1), 403-434, 2016.
  • JL, X. Zhang, Retinex by Higher Order Total Variation L1 Decomposition, Journal of Mathematical Imaging and Vision, 52(3):345-355, 2015.

Conference proceedings

  • JL, J. Fadili and G. Peyré, A Multi-step Inertial Forward–Backward Splitting Method for Non-convex Optimization, Advances in Neural Information Processing Systems (NIPS), 2016.

  • JL, J. Fadili, G. Peyré and R. Luke, Activity Identification and Local Linear Convergence of Douglas– Rachford/ADMM under Partial Smoothness, 5th Int. Conf. on Scale Space and Variational Methods in Computer Vision (SSVM), 2015.
  • JL, J. Fadili and G. Peyré, Locally Linear Convergence of Forward–Backward under Partial Smoothness, Advances in Neural Information Processing Systems (NIPS), 2014.