- Ling Liang, Defeng Sun, and Kim-Chuan Toh. A squared smoothing Newton method for semidefinite programming. Mathematics of Operations Research, 2024. arXiv MOOR
- Shucheng Kang, Xiaoyang Xu, Jay Sarva, Ling Liang, and Heng Yang. Fast and certifiable trajectory optimization, WAFR 2024. arXiv, CODE
- Ling Liang, Haizhao Yang. On the stochastic (variance-reduced) proximal gradient method for regularized expected reward optimization, TMLR 2024. arXiv, TMLR
- Di Hou, Ling Liang, and Kim-Chuan Toh. A sparse smoothing Newton method for solving discrete optimal transport problems, ACM Transactions on Mathematical Software 50, no. 3 (2024): 1–26. arXiv, TOMS
- Lei Yang, Ling Liang, Hong T.M. Chu, and Kim-Chuan Toh. A corrected inexact proximal augmented Lagrangian method with a relative error criterion for a class of group-quadratic regularized optimal transport problems. Journal of Scientific Computing 99, no. 79 (2024). arXiv J. Sci. Comput.
