M. Al-Qizwini, H. Radha, “Truncated and smoothed Schatten-p function for robust tensor recovery”, Annual Conference on Information Sciences and Systems, CISS 2015, pages 1-4, March 2015.
J. Shi, Q. Yin, X. Zheng, W. Yang, “Alternating Direction Method of Multipliers for Generalized Low-Rank Tensor Recovery”, Algorithms 2016, Volume 9, Issue 28, pages 1-16, 2016.
H. Kong, X. Xie, Z. Lin, “t-Schatten-p Norm for Low-Rank Tensor Recovery”, IEEE Journal of Selected Topics in Signal Processing, December 2018.
W. Qin, H. Wang, W. Ma, J. Wang, "Robust High-Order Tensor Recovery via Nonconvex Low-Rank Approximation", IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2022, pages 3633-3637, Singapore, Singapore, 2022.
S. Zhang, L. Han, “Robust tensor recovery with non-convex and non-smooth regularization”, Applied Mathematics and Computation, 2023.
Q. Yu, M. Yang, “Low-rank tensor recovery via non-convex regularization, structured factorization and spatio-temporal characteristics”, Pattern Recognition, Volume 137, May 2023.
X. Chen, J. Zheng, L. Zhao, W. Jiang, X. Zhang, “Orthogonal Tensor Recovery based on Non-Convex Regularization and Rank Estimation”, IEEE Access, January 2024.
Z. Tu, K. Yang, J. Lu, Q. Jiang, “Tensor recovery using the tensor nuclear norm based on nonconvex and nonlinear transformations”, Signal Processing, Volume 219, June 2024.
Y. Liu, Y. Wang, L. Chen, L. Wang, Y. Hu “TIHN: Tensor Improved Huber Norm for Low-rank Tensor Recovery”, International Journal of Wavelets, Multiresolution and Information Processing, May 2024.