论文

Selected Publications: 

[1] Tao, Min; Yuan, Xiaoming. Recovering low-rank and sparse components of matrices from incomplete and noisy observations. SIAM J. Optim. 21 (2011), no. 1, 57–81 (高被引）

[2] He, Bingsheng; Tao, Min; Yuan, Xiaoming. Alternating direction method with Gaussian back substitution for separable convex programming. SIAM J. Optim. 22 (2012), no. 2, 313–340 （高被引）

[3] Chan, Raymond H.; Tao, Min; Yuan, Xiaoming. Constrained total variation deblurring models and fast algorithms based on alternating direction method of multipliers. SIAM J. Imaging Sci. 6 (2013), no. 1, 680–697.  ICCM best paper (国际华人数学家大会最佳论文奖)

[4] Tao, Min; Yuan, Xiaoming. On the O(1/t) convergence rate of alternating direction method with logarithmic-quadratic proximal regularization. SIAM J. Optim. 22 (2012), no. 4, 1431–1448

[5]  Pang, Jong-Shi; Tao, Min. Decomposition methods for computing directional stationary solutions of a class of nonsmooth nonconvex optimization problems. SIAM J. Optim. 28 (2018), no. 2, 1640–1669

[6]  Tao, Min. Minimization of L1 over L2 for sparse signal recovery with convergence guarantee.  SIAM J. Sci. Comput. 44 (2022), no. 2, A770–A797.

[7] Wang, Chao; Tao, Min; Nagy, James G.; Lou, Yifei. Limited-angle CT reconstruction via the L1/L2  minimization. SIAM J. Imaging Sci. 14 (2021), no. 2, 749–777.

[8] Tao, Min; Zhang, Xiao-Ping. Study on L1 over L2 Minimization for Nonnegative Signal Recovery. J. Sci. Comput. 95 (2023), no. 3, Paper No. 94. 

[9]  Wang, Chao; Tao, Min; Chuah, Chen-Nee; Nagy, James; Lou, Yifei. Minimizing L1 over L2 norms on the gradient. Inverse Problems 38 (2022), no. 6, Paper No. 065011, 25 pp.

[10] Tao, Min; Yuan, Xiaoming. On Glowinski's open question on the alternating direction method of multipliers. J. Optim. Theory Appl. 179 (2018), no. 1, 163–196.

[11] Tao, Min; Li, Jiang-Ning. Error bound and isocost imply linear convergence of DCA-based algorithms to D-stationarity. J. Optim. Theory Appl. 197 (2023), no. 1, 205–232. 

[12] Tao, Min; Yuan, Xiaoming. The generalized proximal point algorithm with step size 2 is not necessarily convergent. Comput. Optim. Appl. 70 (2018), no. 3, 827–839.

[13] Tao, Min; Yuan, Xiaoming. On the optimal linear convergence rate of a generalized proximal point algorithm. J. Sci. Comput. 74 (2018), no. 2, 826–850.

[14] He, Bingsheng; Tao, Min; Yuan, Xiaoming. Convergence rate analysis for the alternating direction method of multipliers with a substitution procedure for separable convex programming. Math. Oper. Res. 42 (2017), no. 3, 662–691.

[15] Tao, Min; Yuan, Xiaoming. Accelerated Uzawa methods for convex optimization. Math. Comp. 86 (2017), no. 306, 1821–1845.

[16] Pang, Ming; Gao, Wei; Tao, Min; Zhou, Zhi-Hua. Unorganized malicious attacks detection. In: Advances in Neural Information Processing Systems 31 (NIPS'18), Montreal, Canada, 2018