1. B.S. He, Parallel splitting augmented Lagrangian methods for monotone structured variational inequalities.
Computational Optimization and Applications 42 (2009), 195-212.
2. B.S. He, M. Tao and X.M. Yuan, Alternating Direction Method with Gaussian Back substitution for separable convex programming,
SIAM J. Optim. 22(2012), 313-340.
3. G.Y. Gu, B.S. He and J.F. Yang, Inexact Alternating-Direction-Based Contraction Methods for Separable Linearly Constrained convex optimization
JOTA 163 (2014) 105-129.
4. B.S. He, M. Tao and X.M. Yuan, A splitting method for separable convex programming,
IMA J. Numerical Analysis, 31(2015), 394-426.
5. 何炳生，修正乘子交替方向法求解三个可分离算子的凸优化, 运筹学学报 Vol.19 No.3
6. B.S. He, L.S. Hou, and X.M. Yuan, On Full Jacobian Decomposition of the Augmented Lagrangian Method for Separable Convex Programming,
SIAM J. Optim., 25 (2015) 2274–2312.
7. B.S. He, M. Tao and X. M. Yuan, Convergence rate analysis for the alternating direction method of multipliers with a substitution procedure
for separable convex programming, Mathematics of Operations Research, 42 (2017) 662-691.
8. C.H. Chen, B.S. He, Y.Y. Ye and X. M. Yuan, The direct extension of ADMM for multi-block convex minimization problems is not necessary convergent,
Mathematical Programming, 155 (2016) 57-79.
9. B.S. He, and X. M. Yuan, A class of ADMM-based algorithms for three-block separable convex programming.
Computational Optimization and Applications 70（2018）791–826.
Last Update: Sept. 30, 2019