B.S. He, F. Ma and X.M. Yuan,
Optimally linearizing the alternating direction method of
multipliers for convex
programming, Comput. Optim. Appl. 75
and X.M. Yuan,
Optimal proximal augmented Lagrangian method and its application
to full Jacobian
splitting for multi-block separable convex minimization
problems, IMA Journal of Numerical
Analysis. 40 (2020)，
3 B. S. He, M. H.
Xu and X. M. Yuan, Block-wise ADMM
with a relaxation factor for multiple-block convex programming.
J. Oper. Res. Soc. China 6 (2018), 485-505.
4. B. S. He, My 20 years research on alternating directions
method of multipliers. (Chinese)
Oper. Res. Trans. 22 (2018),
5. B.S. He, and X. M. Yuan, A class of ADMM-based algorithms for
three-block separable convex programming.
Optim. Appl. 70 (2018), 791–826.
6. B. S He, A uniform framework of contraction methods for
convex optimization and monotone variational inequality.
Scientia Sinica Mathematica 48 (2018) 255-272
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. B. S. He, F. Ma and X. M. Yuan, An Agorithmic Framework
of Generalized Primal-Dual Hybrid Gradient Methods for
Saddle Point Problems, J. Math. Imaging Vis. 58 (2017) 279-293.
9. C. H. Chen, X. L. Fu, B.S. He and X. M. Yuan, On
the Iteration Complexity of Some Projection Methods for Monotone
Linear Variational Inequalities, JOTA, 172(2017) 914-928.
10. 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.
11. C.H. Chen, B.S. He, Y.Y. Ye and X. M. Yuan,
The direct extension of ADMM for multi-block convex
problems is not necessary convergent, Mathematical Programming,
155 (2016) 57-79.
12. B.S. He, H.K. Xu and X.M. Yuan, On the Proximal Jacobian
Decomposition of ALM for Multiple-Block Separable
Convex Minimization Problems and its Relationship to ADMM, J.
Sci. Comput. 66 (2016) 1204-1217.
13. B.S. He and X.M. Yuan, Block-wise Alternating Direction
Method of Multipliers for Multiple-block Convex Programming
and Beyond, SMAI J. Computational Mathematics 1 (2015)
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.
15. B.S. He and X. M. Yuan,
On the convergence rate of Douglas-Rachford operator splitting
Programming, 153 (2015) 715-722.
16. 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.
17. 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.
18. B.S. He, M. Tao and X.M. Yuan, A splitting method for
separable convex programming, IMA J. Numerical
19. B. S. He, PPA-like contraction methods for convex
optimization: a framework using variational inequality approach,
Oper. Res. Soc. China 3(2015), 391-420.
20. G.Y. Gu, B.S. He and J.F. Yang, Inexact
Alternating-Direction-Based Contraction Methods for Separable
Constrained Convex Optimization，JOTA 163 (2014) 105-129.
21. B. S. He, Y. F. You and X. M. Yuan, On the Convergence of
Primal-Dual Hybrid Gradient Algorithm, SIAM. J. Imaging
Science 7 (2014), 2526-2537.
22. 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.
23. G.Y. Gu, B.S. He and X.M. Yuan, Customized
proximal point algorithms for linearly constrained convex
and saddle-point problems: a unified approach, Comput. Optim. Appl.,
24. Y. F. You, X.L. Fu and B.S. He,
Lagrangian-PPA based contraction methods for
linearly constrained convex optimization,
Pac. J. Optim. (2014) 199-213.
25. X.J. Cai, G.Y. Gu and B.S. He, On the O(1/t)
convergence rate of the projection and contraction methods for
variational inequalities with Lipschitz continuous monotone
operators, Comput. Optim. Appl.,
He, X.M. Yuan and W.X. Zhang, A customized proximal point
algorithm for convex minimization with linear
constraints, Comput. Optim. Appl.,
27. B.S. He and X.M. Yuan,
Forward-backward-based descent methods for
composite variational inequalities, Optimization
Methods Softw. 28 (2013), 706-724.
28. B.S. He, M. Tao, M.H. Xu and X.M. Yuan, An alternating
direction-based contraction method for linearly constrained
separable convex programming problems, Optimization, 62 (2013),
29. 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.
30. 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.
31. B.S. He and X.M. Yuan, On the $O(1/n)$
Convergence Rate of the Douglas-Rachford
Method，SIAM J. Numer. Anal. 50(2012), 700-709.
32. B.S. He and X.M.Yuan, Convergence analysis of primal-dual
algorithms for a saddle-point problem: From contraction
perspective. SIAM J. Imaging Science. 5(2012), 119-149.
33. C.H. Chen, B.S. He and X.M. Yuan, Matrix completion via
alternating direction methods. IMA Journal of Numerical
Analysis. 32(2012), 227-245.
34. B.S. He, L.Z. Liao and X. Wang, Proximal-like contraction
methods for monotone variational
inequalitiesin a unified
framework I: Effective quadruplet and primary methods, Comput.
35. B.S. He, L.Z. Liao, and X. Wang, Proximal-like contraction
methods for monotone variational
inequalities in a unified
framework II: General methods and numerical experiments, Comput.
36. B.S. He, M.H.
Xu, and X.M. Yuan, Solving large-scale least squares
semidefinite programming by alternating direction
methods. SIAM J. Matrix Anal. Appl. 32(2011), 136-152.
37. B.S. He, W. Xu,
H. Yang, and X.M. Yuan, Solving over-production and
supply-guarantee problems in economic equilibria.
Netw. Spat. Econ. 11(2011), 127-138.
38. M. Tao, B.S.
He, and X.M. Yuan, Solving a class of matrix minimization
problems by linear variational inequality
Linear Alge. Appl. 434(2011), 2343-2352.
39. B.S. He, Z. Peng, and X.F. Wang, Proximal alternating direction-based
contraction methods for separable linearly
constrained convex optimization.
F. M. C. (6)2011, 79-114.
40. X. Wang, B.S.
He, and L.Z. Liao, Steplengths in the extragradient type
methods. J. of Comput. Appl. Math.
233 (2010), 2925-2939.
41. B.S. He, X.Z.
He, and Henry X. Liu, Solving a class of constrained ‘black-box’
inverse variational inequalities.
European J. Oper. Res. 204 (2010), 391-401.
42. X.L. Fu, and
B.S. He, Self-adaptive projection-based prediction correction
method for constrained variational inequalities.
Front. Math. China. 5 (2010), no. 1, 3-21.
43. H. Yang, W. Xu, B.S. He, and Q. Meng, Road pricing for congestion control
with unknown demand and cost functions.
Trans. Res. Part C. 18 (2010), 157-175.
Published papers from 2001 to 2009
Published papers before 2000
Last Update: Sept. 30, 2019