Tian W. Y. and Yuan X. M., Faster alternating direction method of multipliers with O(1/n^2) convergence rate, Mathematics of Computation, under revision; Guo K., Han D. and Yuan X. M., Convergence analysis of Douglas-Rachford splitting method for "strongly + weakly" convex programming, SIAM Journal on Numerical Analysis, under revison; Tian W. Y. and Yuan X. M., Convergence analysis of primal-dual based methods for total variation minimization with finite element approximation, Journal of Scientific Computing, under revision; He B. S., Tao M. and Yuan X. M., Convergence rate and iteration complexity on the alternating direction method of multipliers with a substitution procedure for separable convex programming, Mathematics of Operations Research, to appear; Tao M and Yuan X. M, Accelerated Uzawa methods for convex optimization, Mathematics of Computation, to appear; Dai Y. H., Han D. R., Yuan X. M. and Zhang W. X., A sequential updating scheme of Lagrange multiplier for separable convex programming, Mathematics of Computation, to appear; Tian W. Y. and Yuan X. M., Linearized primal-dual methods for linear inverse problems with total variation regularization and finite element discretization, Inverse Problems, 32, 115011, 2016; He B. S., Ma F. and Yuan X. M., Convergence study on the symmetric version of ADMM with larger step sizes, SIAM Journal on Imaging Sciences, 9(3), 1467-1501, 2016; He B. S., Xu H. K. and Yuan X. M., On the proximal Jacobian decomposition of ALM for multiple-block separable convex minimization problems and its relationship to ADMM, Journal of Scientific Computing, 66, 1204-1217, 2016; Chen C. H., He B. S., Ye Y. Y. and Yuan X. M., The direct extension of ADMM for multi-block convex minimzation problems is not necessarily convergent, Mathematical Programming, 155, 57–79, 2016; Goldstein T., Li M. and Yuan X. M., Adaptive primal-dual hybrid gradient methods for saddle-point problems, NIPS, 2015; He B. S., Hou L. S. and Yuan X. M., On full Jacobian decomposition of the augmented Lagrangian method for separable convex programming, SIAM Journal on Optimization, 25(4), 2274-2312, 2015; Li M. and Yuan X. M., A strictly contractive Peaceman-Rachford splitting method with logarithmic-quadratic proximal regularization for convex programming, Mathematics of Operations Research, 40, 842-858, 2015;