Code & Software

Copyright Notice

All codes and software released here are strictly for academic purposes. Copyright and all rights therein are retained by authors or by other copyright holders. Commercial applications or reproduction are strictly not allowed without the permissions of the authors.

1. Convex Clustering: a MATLAB package for convex clustering.

Citation:

• Defeng Sun, Kim-Chuan Toh, and Yancheng Yuan, Convex clustering: model, theoretical guarantee and efficient algorithm, Journal of Machine Learning Research, 22(9):1−32, 2021.

• Yancheng Yuan, Defeng Sun, and Kim-Chuan Toh, An efficient semismooth Newton based algorithm for convex clustering, International Conference on Machine Learning (ICML), 2018.
  

2. SDPNAL+ : a MATLAB software for semidefinite programming with bound constraints.
   Citation:

• Defeng Sun, Kim-Chuan Toh, Yancheng Yuan, Xinyuan Zhao, SDPNAL+: A Matlab software for semidefinite programming with bound constraints (version 1.0), Optimization Methods and Software, 35 (2020) 87–115.

• Liuqin Yang, Defeng Sun, and Kim-Chuan Toh, SDPNAL+: a majorized semismooth Newton-CG augmented Lagrangian method for semidefinite programming with nonnegative constraints, Mathematical Programming Computation, 7 (2015), pp. 331-366.

• Xinyuan Zhao, Defeng Sun, and Kim-Chuan Toh, A Newton-CG augmented Lagrangian method for semidefinite programming, SIAM Journal on Optimization, 20 (2010), pp. 1737--1765.

3. Nearest Correlation Matrix(Python)

This Python code is based on the following paper:

Houduo Qi and Defeng Sun, A quadratically convergent Newton method for computing the nearest correlation matrix, SIAM Journal on Matrix Analysis and Applications 28 (2006) 360--385.