| Low-rank high-order tensor completion with applications in visual data W Qin, H Wang, F Zhang, J Wang, X Luo, T Huang IEEE Transactions on Image Processing 31, 2433-2448, 2022 | 61 | 2022 |
| Generalized nonconvex approach for low-tubal-rank tensor recovery H Wang, F Zhang, J Wang, T Huang, J Huang, X Liu IEEE Transactions on Neural Networks and Learning Systems 33 (8), 3305-3319, 2021 | 49 | 2021 |
| Low-tubal-rank plus sparse tensor recovery with prior subspace information F Zhang, J Wang, W Wang, C Xu IEEE transactions on pattern analysis and machine intelligence 43 (10), 3492 …, 2020 | 46 | 2020 |
| Robust low-tubal-rank tensor recovery from binary measurements J Hou, F Zhang, H Qiu, J Wang, Y Wang, D Meng IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (8), 4355-4373, 2021 | 36 | 2021 |
| Improved sufficient condition of ℓ1–2‐minimisation for robust signal recovery W Wang, J Wang Electronics Letters 55 (22), 1199-1201, 2019 | 27 | 2019 |
| A nonconvex penalty function with integral convolution approximation for compressed sensing J Wang, F Zhang, J Huang, W Wang, C Yuan Signal Processing 158, 116-128, 2019 | 24 | 2019 |
| LSMM: a statistical approach to integrating functional annotations with genome-wide association studies J Ming, M Dai, M Cai, X Wan, J Liu, C Yang Bioinformatics 34 (16), 2788-2796, 2018 | 23 | 2018 |
| Robust signal recovery with highly coherent measurement matrices W Wang, J Wang, Z Zhang IEEE Signal Processing Letters 24 (3), 304-308, 2016 | 23 | 2016 |
| Guaranteed tensor recovery fused low-rankness and smoothness H Wang, J Peng, W Qin, J Wang, D Meng IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 19 | 2023 |
| Block‐sparse signal recovery via minimisation method W Wang, J Wang, Z Zhang IET Signal Processing 12 (4), 422-430, 2018 | 19 | 2018 |
| Low-rank matrix recovery via regularized nuclear norm minimization W Wang, F Zhang, J Wang Applied and Computational Harmonic Analysis 54, 1-19, 2021 | 17 | 2021 |
| Group sparse recovery in impulsive noise via alternating direction method of multipliers J Wang, J Huang, F Zhang, W Wang Applied and Computational Harmonic Analysis 49 (3), 831-862, 2020 | 17 | 2020 |
| RIP-based performance guarantee for low-tubal-rank tensor recovery F Zhang, W Wang, J Huang, J Wang, Y Wang Journal of Computational and Applied Mathematics 374, 112767, 2020 | 17 | 2020 |
| Fast and efficient algorithm for matrix completion via closed-form 2/3-thresholding operator Z Wang, W Wang, J Wang, S Chen Neurocomputing 330, 212-222, 2019 | 17 | 2019 |
| A perturbation analysis of nonconvex block-sparse compressed sensing J Wang, J Zhang, W Wang, C Yang Communications in Nonlinear Science and Numerical Simulation 29 (1-3), 416-426, 2015 | 16 | 2015 |
| Sharp sufficient condition of block signal recovery via l2 /l1 ‐minimisation J Huang, J Wang, W Wang, F Zhang IET Signal Processing 13 (5), 495-505, 2019 | 13 | 2019 |
| IGESS: a statistical approach to integrating individual-level genotype data and summary statistics in genome-wide association studies M Dai, J Ming, M Cai, J Liu, C Yang, X Wan, Z Xu Bioinformatics 33 (18), 2882-2889, 2017 | 13 | 2017 |
| BIVAS: a scalable Bayesian method for bi-level variable selection with applications M Cai, M Dai, J Ming, H Peng, J Liu, C Yang Journal of Computational and Graphical Statistics 29 (1), 40-52, 2020 | 12 | 2020 |
| Estimating structural missing values via low-tubal-rank tensor completion H Wang, F Zhang, J Wang, Y Wang ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 11 | 2020 |
| One-bit compressed sensing via ℓp (0< p< 1)-minimization method J Hou, J Wang, F Zhang, J Huang Inverse Problems 36 (5), 055005, 2020 | 11 | 2020 |
