Welcome to My Homepage

Background

I received my B.Sc (2011.07) and M.Sc degrees (supervisor: Prof. Zheng-Hai Huang, 2014.07) in Applied Mathematics at Tianjin University. I started my PhD study in 2014.08 in Department of Applied Mathematics at Hong Kong Polytechnic University under supervisions of Prof. Xiaojun Chen (chief-supervisor) and Prof. Ting Kei Pong (co-supervisor). I got my Ph.D. degree in 2017.09. I was a Postdoctoral Fellow from 2017.10 to 2017.12 in Department of Applied Mathematics at Hong Kong Polytechnic University supervised by Prof. Xiaojun Chen, and was a Research Fellow from 2018.01 to 2020.07 in Institute of Operations Research and Analytics at National University of Singapore supervised by Prof. Kim-Chuan Toh, and was a Research Fellow in Department of Mathematics at National University of Singapore supervised by Prof. Kim-Chuan Toh, and was a Research Fellow from 2021.09 to 2022.07 in Department of Applied Mathematics at Hong Kong Polytechnic University supervised by Prof. Xiaojun Chen. I am now a tenure-track associate professor in School of Computer Science and Engineering at Sun Yat-Sen University.

This is my CV.

Research Interests

Broadly speaking: Algorithm design, optimization theory, and applications

Current focus:

• Practical inexact methods for convex or nonconvex optimization problems in data science and machine learning

• Optimization methods in computational optimal transport

Preprints

1. Lei Yang, Jingjing Hu and Kim-Chuan Toh. An inexact Bregman proximal difference-of-convex algorithm with two types of relative stopping criteria. 2024.

2. Lei Yang and Kim-Chuan Toh. Inexact Bregman proximal gradient method and its inertial variant with absolute and relative stopping criteria. 2023.

Publications

1. 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, 99:76, 2024. [arXiv]

2. Lei Yang. Proximal gradient method with extrapolation and line search for a class of nonconvex and nonsmooth problems. Journal of Optimization Theory and Applications, 200(1): 68-103, 2024. [arXiv] [codes]

3. 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(1): 107-146, 2023. [arXiv]

4. Lei Yang and Kim-Chuan Toh. Bregman proximal point algorithm revisited: A new inexact version and its inertial variant. SIAM Journal on Optimization, 32(3): 1523--1554, 2022. [arXiv]

5. Lei Yang, Xiaojun Chen and Shuhuang Xiang. Sparse solutions of a class of constrained optimization problems. Mathematics of Operations Research, 47(3): 1932-1956, 2022. [arXiv]

6. Lei Yang, Jia Li, Defeng Sun and Kim-Chuan Toh. A fast globally linearly convergent algorithm for the computation of Wasserstein barycenters. Journal of Machine Learning Research, 22(21): 1–37, 2021. [arXiv]

7. Lei Yang, Ting Kei Pong and Xiaojun Chen. A non-monotone alternating updating method for a class of matrix factorization problems. SIAM Journal on Optimization, 28(4): 3402--3430, 2018. [arXiv] [codes]

8. Lei Yang, Ting Kei Pong and Xiaojun Chen. Alternating direction method of multipliers for a class of nonconvex and nonsmooth problems with applications to background/foreground extraction. SIAM Journal on Imaging Sciences, 10(1): 74--110, 2017. [arXiv] [local pdf file]

9. Lei Yang, Zheng-Hai Huang, Shenglong Hu and Jiye Han. An iterative algorithm for third-order tensor multi-rank minimization. Computational Optimization and Applications, 63(1): 169--202, 2016. [local pdf file]

10. Xian-Jun Shi, Lei Yang and Zheng-Hai Huang. A fixed point method for the linear complementarity problem arising from American option pricing. Acta Mathematicae Applicatae Sinica, English Series, 32(4): 921--932, 2016. [local pdf file]

11. Min Zhang, Lei Yang and Zheng-Hai Huang. Minimum n-rank approximation via iterative hard thresholding. Applied Mathematics and Computation, 256: 860--875, 2015. [arXiv] [local pdf file]

12. Lei Yang, Zheng-Hai Huang and Yu-Fan Li. A splitting augmented Lagrangian method for low multilinear-rank tensor recovery. Asia-Pacific Journal of Operational Research, 32(1): 1540008 (25p), 2015. [arXiv] [local pdf file]

13. Lei Yang, Zheng-Hai Huang and XianJun Shi. A fixed point iterative method for low n-rank tensor pursuit. IEEE Transactions on Signal Processing, 61(11): 2952--2962, 2013. [local pdf file]

Talks

1. MOS2023 (Young Plenary Talk), Bregman proximal point algorithm revisited: A new inexact version and its inertial variant, Chendu, May 2023. 

2. ICCOPT 2019, A fast globally linearly convergent algorithm for the computation of Wasserstein barycenters, Berlin, August 2019.

3. 2018 INFORMS Annual Meeting, A fast globally linearly convergent algorithm for the computation of Wasserstein barycenters, Phoenix, November 2018.

4. Workshop on New Optimization Methods, A non-monotone alternating updating method for a class of matrix factorization problems, Hong Kong, November 2017.

5. 2017 Imaging Science Camp, A non-monotone alternating updating method for a class of matrix factorization problems, Shenzhen, March 2017.

6. ICCOPT 2016, ADMM for a class of nonconvex and nonsmooth problems with applications to background/foreground extraction, Tokyo, August 2016.

7. SIAM Annual Meeting 2016 (Student Discuss Section), ADMM for a class of nonconvex and nonsmooth problems with applications to background/foreground extraction, Boston, July 2016.

8. HKMS Annual General Meeting 2015, Alternating direction method of multipliers for nonconvex background/foreground extraction, Hong Kong, May 2015.

9. SIAM-IS 2014, Minimum n-rank approximation via iterative hard thresholding, Hong Kong, May 2014.

Visits

1. 2016.03 -- 2016.07, University of California, Davis (UCD), hosted by Prof. Michael P. Friedlander.

Links

• My link on Google Scholar