1. B.S. He and H. Yang, Some convergence properties of a method of multipliers for linearly constrained monotone variational inequalities,
Operations Research Letters, 23, pp. 151-161, 1998.
2. B.S. He, H. Yang and S.L. Wang, Alternating directions method with self-adaptive penalty parameters for monotone variational inequalities,
Journal of Optimization Theory and applications, 106, pp. 349--368, 2000.
3. B.S. He,, L-Z Liao, D.R. Han and H. Yang, A new inexact alternating directions method for monotone variational inequalities,
Mathematical Programming, 92, pp. 103-118, 2002
4. B.S. He, S.L. Wang and H. Yang, A modified variable-penalty alternating directions method for monotone variational inequalities,
J. Computational Mathematics, 21, pp. 495-504, 2003
5. B. S. He, L-Z. Liao and M. J. Qian, Alternating projection based prediction-correction methods for structured variational inequalities,
Journal of Computational Mathematics, 24(6), 693-710, 2006.
6. B.S. He and X.M. Yuan, On the O(1/n) Convergence Rate of the Douglas-Rachford Alternating Direction Method,
SIAM J. Numer. Anal. 50(2012), 700-709
7. X.J. Cai, G.Y. Gu, B.S. He and X.M. Yuan, A proximal point algorithms revisit on the alternating direction method of multipliers,
Science China Mathematics, 56 (2013), 2179-2186.
8. B. S. He, H. Liu, Z.R. Wang and X. M. Yuan, A strictly Peaceman-Rachford splitting method for convex programming,
SIAM J. Optim. 24 (2014),1011-1040.
9. B.S. He and X.M. Yuan, On non-ergodic convergence rate of Douglas-Rachford alternating directions method of multipliers,
Numerische Mathematik, 130 (2015) 567-577.
10. B.S. He and X. M. Yuan, On the convergence rate of Douglas-Rachford operator splitting method,
Mathematical Programming, 153 (2015) 715-722.
11. E.X. Fang, B.S. He, H. Liu and X. M. Yuan, Generalized alternating direction method of multipliers:
new theoretical insights and applications, Mathematical Programming Computation, 7 (2015) 149-187.
12. B. S. He, F. Ma and X. M. Yuan, Convergence study on the symmetric version of ADMM with larger step sizes,
SIAM. J. Imaging Science 9 (2016) 1467-1501.
13 B. S. He, F. Ma and X. M. Yuan, Optimally linearizing the ADMM for the convex programming
Computational Optimization and Applications 75(2020) 361-388