[1] Lei Y, Liao A P. A minimal residual algorithm for the inconsistent matrix equation AXB=C over symmetric matrices[J]. Applied Mathematics and Computation, 2007, 188:499-513.[2] Li J F, Hu X Y, Zhang L. Numerical solutions of AXB=C for centrosymmetric matrix X under a specified submatrix constraint[J]. Numerical Linear Algebra with Application, 2011, 18:857-873.[3] Peng Y X, Hu X Y, Zhang L. An iteration method for the symmetric solutions and the optimal approximation solution of the matrix equation AXB=C[J]. Applied Mathematics and Computation, 2005, 160:763-777.[4] Qiu Y Y, Zhang Z Y, Lu J F. Matrix iterative solutions to then least squares problem of BXAT=F with some linear constraints[J]. Applied Mathematics and Computation, 2007, 185:284-300.[5] Ding F, Chen T W. On iterative solutions of general coupled matrix equations[J]. SIAM Joural on Control and Optimization, 2006, 44:2269-2284.[6] Bouhamidi A, Jbilou K, Raydan M. Convex constrained optimization for large-scale generalized Sylvester equations[J]. Computational Optimization and Applications, 2011, 48:233-253.[7] Bouhamidi A, Enkhbat R, Jbilou K. Conditional gradient Tikhonov method for a convex optimization problem in image restoration[J]. Journal of Computational and Applied Mathematics, 2014, 255:580-592.[8] Birgin E G, Martinezand J M, Raydan M. Inexact Spectral Projected Gradient methods on convex sets[J]. SIMA Journal on Numerical Analysis, 2003, 23:539-559.[9] Escalante R, Raydan M. Dykstra's algorithm for constrained least-squares rectangular matrix problems[J]. Computers Mathematics with Applications, 1998, 6:73-79.[10] Li J F, Hu X Y, Zhang L. Dykstra's algorithm for constrained least-squares doubly symmetric matrix problems[J]. Theoretical Computer Science, 2010, 411:2818-2826.[11] Yang J F. Yuan X M. Linearized augmented lagrangian and alternating direction methods for nuclear norm minimization[J]. Mathematics of Computation, 2012, 82:301-329.[12] Xiao Y H, Jin Z F. An alternating direction method for linear-constrained matrix nuclear norm minimization[J]. Numerical Linear Algebra with Application, 2012, 19:541-554.[13] Li Q N. Alternating direction method for a class of constrained matrix approximation problems[J]. Pacific Journal of Optimization, 2012, 8:765-778.[14] Boyd S, Parikh N, Chu E, Peleato B, Eckstein J. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers[J]. Foundations and Trends in Machine Learning, 2011, 3:1-122.[15] Boley D. Local linear convergence of ADMM on quadratic or linear programs[J]. SIAM Joural on Control and Optimization, 2013, 23:2183-2207.[16] Han D R, Yuan X M. Local linear convergence of the alternating direction method of multipliers for quadratic programs[J]. SIAM Journal on Numerical Analysis, 2013, 51:3446-3457.[17] He B S, Yang H, Wang S L. Alternating directions method with self-adaptive penalty parameters for monotone variational inequalities[J]. Journal of Optimization Theory and Applizations, 2000, 106:337-356.[18] Michael NG K, Wang F, Yuan X M. Inexact alternating direction methods for image recovery[J]. SIAM Journal on Scientific Computing, 2011, 33:1643-1668.[19] Birgin E G, Mart'?nez J M, Raydan M. Nonmonotone spectral projected gradient methods on convex sets[J]. SIAM Journal on Optimization, 2000, 10:1196-1211.[20] Paige C C, Saunders A. LSQR:An algorithm for sparse linear equations and sparse least squares[J]. ACM Transactions on Mathematmal Software, 1982, 8:43-71.[21] Peng Z Y. Solutions of symmetry-constrained least-squares problems[J]. Numerical Linear Algebra with Applications, 2008, 15:373-389.[22] Li S K, Huang T Z. LSQR iterative method for generalized coupled Sylvester matrix equations[J]. Applied Mathematical Modelling, 2012, 36:3545-3554.[23] Goldstein T, O'onoghue B, Setzer S, Baraniuk R. Fast alternating direction optimization methods[J], SIAM Journal on Imaging Sciences. 2014, 7:1588-1623. |