Robust Outlier Estimation for Low Rank Matrix Recovery

X. Zhang, Y. Gao, L. Lan, X. Guo, X.  Huang, Z. Luo, “Low-Rank Matrix Recovery via Continuation-Based Approximate Low-Rank Minimization”, Pacific Rim International Conference on Artificial Intelligence, PRICAI 2018, pages 559-573, July 2018.

X. Guo, Z. Lin, "ROUTE: Robust Outlier Estimation for Low Rank Matrix Recovery", International Joint Conference on Artificial Intelligence, IJCAI 2017, pages 1746-1752, Melbourne, Australia, 2017.

X. Guo, Z. Lin, “Low-Rank Matrix Recovery via Robust Outlier Estimation”, IEEE Transactions on Image Processing, Volume 27, No. 11, pages 5316-5327, November 2018.

J. Ma, S. Fattahi, “Global Convergence of Sub-gradient Method for Robust Matrix Recovery: Small Initialization, Noisy Measurements, and Over-parameterization”, Preprint, February 2022.

H. Zhang, F. Qiang, P. Shi, W. Du, Y Tang, J Qian, C Gong, "Generalized Nonconvex Nonsmooth Low-Rank Matrix Recovery Framework with Feasible Algorithm Designs and Convergence Analysis", IEEE Transactions on Neural Networks and Learning Systems, 2022.

Z. Wang, H. So, A. Zoubir, "Robust Low-Rank Matrix Recovery via Hybrid Ordinary-Welsch Function”, IEEE Transactions on Signal Processing, Volume 71, pages 2548-2563, 2023.

X. Liu, Y. Dou, J. Wang, “Modified correlated total variation regularization for low-rank matrix recovery”, Signal, Image and Video Processing, June 2024.