Ling LIANG (梁令)

Ling LIANG (梁令)

Postdoctoral Associate

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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

Future Blog Post

less than 1 minute read

Published:

This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

publications

2021

  • Ling Liang, Defeng Sun, and Kim-Chuan Toh. An inexact augmented Lagrangian method for second-order cone programming with applications. SIAM Journal on Optimization 31, no. 3 (2021): 1748-1773. arXiv, SIOPT

2022

  • Ling Liang, Xudong Li, Defeng Sun, and Kim-Chuan Toh. QPPAL: A two-phase proximal augmented Lagrangian method for high dimensional convex quadratic programming problems. ACM Transactions on Mathematical Software 48, no. 3 (2022): 1-27. arXiv, TOMS, CODE
  • Ying Cui, Ling Liang, Defeng Sun, and Kim-Chuan Toh. On degenerate doubly nonnegative projection problems. Mathematics of Operations Research 47, no. 3 (2022): 2219-2239. arXiv, MOOR
  • Quoc Tran-Dinh, Ling Liang, and Kim-Chuan Toh. A new homotopy proximal variable-metric framework for composite convex minimization. Mathematics of Operations Research 47, no. 1 (2022): 508-539. arXiv, MOOR

2023

  • Hong T.M. Chu, Ling Liang, Kim-Chuan Toh, and Lei Yang. An efficient implementable inexact entropic proximal point algorithm for a class of linear programming problems. Computational Optimization and Applications 85, no. 1 (2023): 107–146. arXiv, COAP, CODE
  • Heng Yang, Ling Liang, Luca Carlone, and Kim-Chuan Toh. An inexact projected gradient method with rounding and lifting by nonlinear programming for solving rank-one semidefinite relaxation of polynomial optimization. Mathematical Programming 201, no. 1–2 (2023): 409–472. arXiv, MP, CODE

2024

  • Ling Liang, Defeng Sun, and Kim-Chuan Toh. A squared smoothing Newton method for semidefinite programming. Mathematics of Operations Research, 2024 (Accepted). 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, 2024. 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.

Pre-prints

  • Ling Liang, Haizhao Yang. PNOD: An efficient projected Newton framework for exact optimal experimental designs, 2024. arXiv
  • Ling Liang, Cameron Austin, and Haizhao Yang. Accelerating multi-block constrained optimization through learning to optimize, 2024. arXiv
  • Ling Liang, Kim-Chuan Toh, and Haizhao Yang. Vertex exchange method for a class of convex quadratic programming problems, 2024. arXiv
  • Ling Liang, Qiyuan Pang, Kim-Chuan Toh, and Haizhao Yang. Nesterov’s accelerated Jacobi-type methods for large-scale symmetric positive semidefinite linear systems, 2024. arXiv
  • Ling Liang, Kim-Chuan Toh, and Jia-Jie Zhu. An inexact Halpern iteration with application to distributionally robust optimization, 2024. arXiv
  • Ching-pei Lee, Ling Liang, Tianyun Tang, and Kim-Chuan Toh. Accelerating nuclear-norm regularized low-rank matrix optimization through Burer-Monteiro decomposition, 2023. arXiv

talks

teaching