Professor Bingsheng He

        52.  B.S. He, F. Ma, S.J. Xu  and X.M. Yuan, A rank-two relaxed parallel splitting version of the augmented Lagrangian

            method with step size in (0,2) for separable convex programming, Mathematics of Computation, 92(2023), 1633-1663.

       51.  B.S. He, S.J. Xu  and X.M. Yuan, Extensions of ADMM for separable convex optimization problems with linear

             equality or inequality constraints, Handbook of Numerical Analysis, 24 (2023) 511-557.  arXiv:2107.01897v2[math.OC].

       50. B.S. He, Using a unified framework to design the splitting and contraction methods for convex optimization (in Chinese).

            Numerical Mathematics - A Journal of Chinese Universities, 44 (2022), 1-35   Paper Download

       49. B.S. He, F. Ma, S.J. Xu  and X.M. Yuan, A generalized primal-dual algorithm with improved convergence condition

            for saddle point problems. SIAM J Imaging Sci., 15(3), 1157-1183 (2022) 

      48. B.S. He, S.J. Xu,  X.M. Yuan,  On Convergence of the Arrow–Hurwicz Method for Saddle Point Problems. J Math

             Imaging Vis 64, 662–671 (2022).

      47. B.S. He and X.M. Yuan, On the optimal proximal parameter of an ADMM-like splitting method for separable

             convex programming. Mathematical methods in image processing and inverse problems, 139–163, Springer Proc.

             Math. Stat., 360.  Springer, Singapore, 2021.

      46. S.J. Xu and B.S. He, A parallel splitting ALM-based algorithm for separable convex programming,  Comput. Optim.

            Appl. 80 (2021),  831–851.

      45. B.S. He, Study on the Splitting Methods for Separable Convex Optimization in a Unified Algorithmic Framework,

           Analysis in Theory and Applications, 26 (2020) 262-282. 

     44. B.S. He, F. Ma and X.M. Yuan, Optimally linearizing the alternating direction method of multipliers for convex

            programming,  Comput. Optim. Appl. 75 (2020), 361-388.

     43. B.S. He,  F. Ma  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)，

           1188-1216.

     42. 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. 

     41. B. S. He, My 20 years research on alternating directions method of multipliers. (Chinese) Oper. Res. Trans.  22 (2018),

          1–31.    

     40. B.S. He, and X. M. Yuan, A class of ADMM-based algorithms for three-block separable convex programming.

           Comput. Optim. Appl. 70 (2018),  791–826.

     39. B. S He, A uniform framework of contraction methods for convex optimization and monotone variational inequality.

          (Chinese)  Scientia Sinica Mathematica 48 (2018)  255-272

     38. 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.

     37.  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.

     36. 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.

     35. 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.

     34. 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.

     33. 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.

     32.  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) 145-174.       

     31. 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.

     30. B.S. He and X. M. Yuan, On the convergence rate of Douglas-Rachford operator splitting method, Mathematical

           Programming, 153 (2015) 715-722.

     29. 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.

     28. 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.

     27. B.S. He, M. Tao and X.M. Yuan, A splitting method for separable convex programming, IMA J. Numerical  Analysis,

           31(2015), 394-426.

     26. B. S. He, PPA-like contraction methods for convex optimization: a framework using variational inequality approach, J.

           Oper. Res. Soc. China 3(2015), 391-420.

     25. 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.

     24. 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.

     23.  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.

     22.  G.Y. Gu, B.S. He and X.M. Yuan,  Customized proximal point algorithms  for linearly constrained convex minimization

            and saddle-point problems: a unified approach,  Comput. Optim. Appl., 59(2014), 135-161.

     21. 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.

     20. 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., 57(2014), 339-363.

     19. B.S. He, X.M. Yuan and W.X. Zhang, A customized proximal point algorithm for convex minimization with linear

            constraints,  Comput. Optim. Appl., 56(2013), 559-572.

     18. B.S. He and X.M. Yuan, Forward-backward-based descent methods for composite variational inequalities, Optimization

           Methods Softw. 28 (2013), 706-724.

     17. 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), 573-596.

     16. 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.

     15. B.S. He and X.M. Yuan, An accelerated inexact proximal point algorithm for convex minimization，JOTA 154 (2012),

            536-548.

     14.  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.      13. 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.

     12. 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.

     11. 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.

    10. 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. Optim. Appl., 51(2012), 649-679.

     9. 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. Optim. Appl., 51(2012),  681-708.

     8. 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.

     7. 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.

     6. M. Tao, B.S. He, and X.M. Yuan, Solving a class of matrix minimization problems by linear variational inequality

           approaches.  Linear Alge. Appl. 434(2011), 2343-2352.

     5. 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.

     4. X. Wang, B.S. He, and L.Z. Liao,  Steplengths in the extragradient type methods. J. of Comput. Appl. Math.

           233 (2010), 2925-2939.

     3. 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.

     2. 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.

     1. 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: Nov. 28, 2023