[1] 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 R in Machine Learning, 2011, 3(1):1-122.[2] Eckstein J, Bertsekas D P. On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators[J]. Mathematical Programming, 1992, 55(1):293-318.[3] Fang E X, He B S, Liu H, Yuan X M. Generalized alternating direction method of multipliers:new theoretical insights and applications[J]. Mathematical Programming Computation, 2015, 7(2):149-187.[4] Gabay D, Mercier B. A dual algorithm for the solution of nonlinear variational problems via finite element approximation[J]. Computers and Mathematics with Applications, 1976, 2(1):17-40.[5] Gao B, Ma F. Symmetric alternating direction method with indefinite proximal regularization for linearly constrained convex optimization[J]. Journal of Optimization Theory and Applications, 2018, 176(1):1-27.[6] Glowinski R, Marroco A. Sur l'approximation, par éléments finis d'ordre un, et la résolution, par pénalisation-dualité d'une classe de problèmes de Dirichlet non linéaires[J]. Revue Française d'Automatique, Informatique, Recherche Opérationelle, 1975, 2:41-76.[7] Hansen P C, Nagy J G, O'Leary D P. Deblurring images:matrices, spectra, and filtering[M]. SIAM, Philadelphia, 2006.[8] He B S. PPA-like contraction methods for convex optimization:a framework using variational inequality approach[J]. Journal of Operations Research Society of China, 2015, 3(4):391-420.[9] He B S, Ma F, Yuan X M. Linearized alternating direction method of multipliers via positiveindefinite proximal regularization for convex programming[J/OL]. http://www.optimizationonline.org, 2016-07-31.[10] He B S, Xu M H, Yuan X M. Solving large-scale least squares semidefinite programming by alternating direction methods[J]. SIAM Journal on Matrix Analysis and Applications, 2011, 32(1):136-152.[11] Li M, Li X X, Yuan X M. Convergence analysis of the generalized alternating direction method of multipliers with logarithmic-quadratic proximal regularization[J]. Journal of Optimization Theory and Applications, 2015, 164(1):218-233.[12] Recht B, Fazel M, Parrilo P A. Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization[J]. SIAM Review, 2010, 52(3):471-501.[13] Tao M, Yuan X M. Recovering low-rank and sparse components of matrices from incomplete and noisy observations[J]. SIAM Journal on Optimization, 2011, 21(1):57-81.[14] Tibshirani R J. Regression shrinkage and selection via the lasso[J]. Journal of the Royal Statistical Society. Series B, 1996, 267-288.[15] Yang J F, Yuan X M. Linearized augmented lagrangian and alternating direction methods for nuclear norm minimization[J]. Mathematics of Computation, 2013, 82(281):301-329. |