On the Convergence Properties of a Majorized Alternating Direction Method of Multipliers for Linearly Constrained Convex Optimization Problems with Coupled Objective Functions. - Ying Cui 004; Xudong Li 004; Defeng Sun; Kim-Chuan Toh (J. Optim. Theory Appl., 2016)

A Schur complement based semi-proximal ADMM for convex quadratic conic programming and extensions. - Xudong Li 004; Defeng Sun; Kim-Chuan Toh (Math. Program., 2016)

Estimation of Markov Chain via Rank-constrained Likelihood. - Xudong Li 004; Mengdi Wang; Anru Zhang (ICML, 2018)

QSDPNAL: a two-phase augmented Lagrangian method for convex quadratic semidefinite programming. - Xudong Li 004; Defeng Sun; Kim-Chuan Toh (Math. Program. Comput., 2018)

A Highly Efficient Semismooth Newton Augmented Lagrangian Method for Solving Lasso Problems. - Xudong Li 004; Defeng Sun; Kim-Chuan Toh (SIAM J. Optim., 2018)

On Efficiently Solving the Subproblems of a Level-Set Method for Fused Lasso Problems. - Xudong Li 004; Defeng Sun; Kim-Chuan Toh (SIAM J. Optim., 2018)

A block symmetric Gauss-Seidel decomposition theorem for convex composite quadratic programming and its applications. - Xudong Li 004; Defeng Sun; Kim-Chuan Toh (Math. Program., 2019)

On the efficient computation of a generalized Jacobian of the projector over the Birkhoff polytope. - Xudong Li 004; Defeng Sun; Kim-Chuan Toh (Math. Program., 2020)

An Asymptotically Superlinearly Convergent Semismooth Newton Augmented Lagrangian Method for Linear Programming. - Xudong Li 004; Defeng Sun; Kim-Chuan Toh (SIAM J. Optim., 2020)

Fast Algorithms for Stackelberg Prediction Game with Least Squares Loss. - Jiali Wang; He Chen; Rujun Jiang; Xudong Li 004; Zihao Li (ICML, 2021)

On the equivalence of inexact proximal ALM and ADMM for a class of convex composite programming. - Liang Chen 006; Xudong Li 004; Defeng Sun; Kim-Chuan Toh (Math. Program., 2021)

Solving Stackelberg Prediction Game with Least Squares Loss via Spherically Constrained Least Squares Reformulation. - Jiali Wang; Wen Huang 001; Rujun Jiang; Xudong Li 004; Alex L. Wang (ICML, 2022)

Learning Markov Models Via Low-Rank Optimization. - Ziwei Zhu; Xudong Li 004; Mengdi Wang; Anru Zhang (Oper. Res., 2022)

QPPAL: A Two-phase Proximal Augmented Lagrangian Method for High-dimensional Convex Quadratic Programming Problems. - Ling Liang; Xudong Li 004; Defeng Sun; Kim-Chuan Toh (ACM Trans. Math. Softw., 2022)

Hölderian Error Bounds and Kurdyka-Łojasiewicz Inequality for the Trust Region Subproblem. - Rujun Jiang; Xudong Li 004 (Math. Oper. Res., 2022)

Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-Order Convergence. - Yuetian Luo; Wen Huang 001; Xudong Li 004; Anru Zhang (Oper. Res., 2024)

On Geometric Connections of Embedded and Quotient Geometries in Riemannian Fixed-Rank Matrix Optimization. - Yuetian Luo; Xudong Li 004; Anru R. Zhang (Math. Oper. Res., 2024)

Nonconvex Factorization and Manifold Formulations Are Almost Equivalent in Low-Rank Matrix Optimization. - Yuetian Luo; Xudong Li 004; Anru R. Zhang (INFORMS J. Optim., 2025)

Data-Driven Minimax Optimization with Expectation Constraints. - Shuoguang Yang; Xudong Li 004; Guanghui Lan (Oper. Res., 2025)