| Generalized Symmetric ADMM for Separable Convex Optimization J Bai, J Li, F Xu, H Zhang Computational Optimization and Applications, 2017 | 76 | 2017 |
| An inexact accelerated stochastic ADMM for separable convex optimization J Bai, WW Hager, H Zhang Computational Optimization and Applications 81 (2), 479-518, 2022 | 58 | 2022 |
| A preconditioned two-step modulus-based matrix splitting iteration method for linear complementarity problem PF Dai, J Li, J Bai, J Qiu Applied Mathematics and Computation 348, 542-551, 2019 | 31 | 2019 |
| A new model for sparse and low-rank matrix decomposition ZS Liu, JC Li, G Li, JC Bai, XN Liu J. Appl. Anal. Comput 7 (2), 600-616, 2017 | 27 | 2017 |
| A parametrized proximal point algorithm for separable convex optimization JC Bai, H Zhang, JC Li Optimization Letters, 2017 | 27 | 2017 |
| Convergence on a symmetric accelerated stochastic ADMM with larger stepsizes J Bai, D Han, H Sun, H Zhang arXiv preprint arXiv:2103.16154, 2021 | 25 | 2021 |
| A general preconditioner for linear complementarity problem with an M-matrix PF Dai, JC Li, YT Li, J Bai Journal of Computational and Applied Mathematics 317, 100-112, 2017 | 15 | 2017 |
| On the low rank solution of the Q‐weighted nearest correlation matrix problem XF Duan, JC Bai, JF Li, JJ Peng Numerical linear algebra with applications 23 (2), 340-355, 2016 | 12 | 2016 |
| A new insight on augmented Lagrangian method with applications in machine learning J Bai, L Jia, Z Peng Journal of Scientific Computing 99 (2), 53, 2024 | 10 | 2024 |
| On the generalized low rank approximation of the correlation matrices arising in the asset portfolio X Duan, J Bai, M Zhang, X Zhang Linear Algebra and its Applications 461, 1-17, 2014 | 10 | 2014 |
| Iteration complexity analysis of a partial LQP-based alternating direction method of multipliers J Bai, Y Ma, H Sun, M Zhang Applied Numerical Mathematics 165, 500-518, 2021 | 9 | 2021 |
| Linearized symmetric multi-block ADMM with indefinite proximal regularization and optimal proximal parameter X Chang, J Bai, D Song, S Liu Calcolo 57, 1-36, 2020 | 9 | 2020 |
| New error bounds for linear complementarity problems of S-Nekrasov matrices and B–S-Nekrasov matrices PF Dai, J Li, J Bai, L Dong Computational and Applied Mathematics 38, 1-14, 2019 | 7 | 2019 |
| Accelerated Stochastic Peaceman–Rachford Method for Empirical Risk Minimization JC Bai, FM Bian, XK Chang, L Du Journal of the Operations Research Society of China 11 (4), 783-807, 2023 | 6 | 2023 |
| Convergence revisit on generalized symmetric ADMM J Bai, X Chang, J Li, F Xu Optimization 70 (1), 149-168, 2021 | 6 | 2021 |
| A joint analysis of multi-paradigm fMRI data with its application to cognitive study Y Bai, Y Gong, J Bai, J Liu, HW Deng, V Calhoun, YP Wang IEEE transactions on medical imaging 40 (3), 951-962, 2020 | 6 | 2020 |
| Notes on new error bounds for linear complementarity problems of Nekrasov matrices, B-Nekrasov matrices and QN-matrices PF Dai, J Li, J Bai, L Dong Numer Math Theory Methods Appl 12, 1191-1212, 2019 | 6 | 2019 |
| Accelerated symmetric ADMM and its applications in signal processing J Bai, J Liang, K Guo, Y Jing arXiv preprint arXiv:1906.12015, 2019 | 6 | 2019 |
| Several variants of the primal-dual hybrid gradient algorithm with applications J Bai, J Li, F Xu Optimization Online 2 (2), 1.2, 2017 | 6 | 2017 |
| An inexact ADMM with proximal-indefinite term and larger stepsize Y Ma, J Bai, H Sun Applied Numerical Mathematics 184, 542-566, 2023 | 5 | 2023 |
hongchao ZhangLouisiana State UniversityVerified email at math.lsu.edu