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News

• [July 1st, 2022] New preprint "Doubly majorized algorithm for sparsity-inducing optimization problems with regularizer-compatible constraints ".

• [June 14, 2022] Our paper ''Convergence analysis under consistent error bounds '' has been accepted for publication in Foundations of Computational Mathematics. [link] 

• [Feb 3rd, 2022] Our paper ''An inexact successive quadratic approximation method for a class of difference-of-convex optimization problems'' has been accepted for publication in Computational Optimization and Applications. [link] 

• [April 1st, 2021] I move to Tokyo Institute of Technology. 

Background

I received my Bachelor degree in July 2010 from Wuhan University, School of Mathematics and Statistics. I started my Master study in  September 2010 in  Chinese Academy of Sciences, Academy of Mathematics and Systems Science,  and became a PhD candidate there in September 2012, under the supervision of Professor Yu-Hong Dai. I got my PhD degree in Computational Mathematics in July 2015. I was  a Postdoctoral Fellow in Department of Applied Mathematics at The Hong Kong Polytechnic University from March 2016 to August 2018, under the mentorship of Professor Ting Kei Pong. I was a Postdoctoral Researcher from September 2018 to March 2021 in RIKEN AIP Center hosted by Professor Akiko Takeda. I am currently an assistant professor at Tokyo Institute of Technology. 

This is my CV.

Research Interests

Nonconvex optimization: algorithm and analysis

Publications

1.  Tianxiang Liu, Ting Kei Pong and Akiko Takeda. Doubly majorized algorithm for sparsity-inducing optimization problems with regularizer-compatible constraints. To appear in Comput. Optim. Appl.. [code] 

2. Tianxiang Liu and Bruno F. Lourenço. Convergence analysis under consistent error bounds.  Found. Comput. Math., DOI: 10.1007/s10208-022-09586-4.

3. Tianxiang Liu and Akiko Takeda. An inexact successive quadratic approximation method for a class of difference-of-convex optimization problems. Comput. Optim. Appl. 82,  pp. 141-173, 2022. [code] 

4. Tianxiang Liu, Ivan Markovsky, Ting Kei Pong and Akiko Takeda. A hybrid penalty method for a class of optimization problems with multiple rank constraints. SIAM J. Matrix Anal. A. 41, pp. 1260-1283, 2020. [code]

5. Ivan Markovsky, Tianxiang Liu and Akiko Takeda. Data-driven structured noise filtering via common dynamics estimation.  IEEE Trans. Signal Process, 68,  pp. 3064-3073, 2020.

6. Tianxiang Liu, Zhaosong Lu, Xiaojun Chen and Yu-Hong Dai. An exact penalty method for semidefinite-box constrained low-rank matrix optimization problems. IMA J. Numer. Anal. 40, pp. 563-586, 2020.

7. Tianxiang Liu, Ting Kei Pong and Akiko Takeda. A refined convergence analysis of pDCAe with applications to simultaneous sparse recovery and outlier detection. Comput. Optim. Appl. 73,  pp. 69-100, 2019.

8. Tianxiang Liu, Ting Kei Pong and Akiko Takeda. A successive difference-of-convex approximation method for a class of nonconvex nonsmooth optimization problems. Math. Program. 176,  pp. 339–367, 2019.  

9. Guoyin Li, Tianxiang Liu and Ting Kei Pong. Peaceman-Rachford splitting for a class of nonconvex optimization problems.  Comput. Optim. Appl. 68, pp. 407-436, 2017. 

10. Tianxiang Liu and Ting Kei Pong. Further properties of the forward-backward envelope with applications to difference-of-convex programming. Comput. Optim. Appl. 67, pp. 489-520, 2017.

Talks

1. RAMP2023. エラーバウンド, 正則変動及び明示的な収束率 , 東京, 2023年11月20-21日.

2. 日本OR学会2021年秋季研究発表会. DC問題に対する非厳密Newton型近接勾配法, 東京 (zoom), 2021年９月16日-17日.

3. OP21. Convergence analysis under consistent error bounds, Online (zoom), July 20-23, 2021.

4. 日本OR学会2021年春季研究発表会. 穏当なエラーバウンドと収束解析, 東京 (zoom), 2021年３月2日-3日.

5. ICCOPT2019. A successive difference-of-convex approximation method with applications to control problems, Berlin, August 3-8, 2019. 

6. EURO2018. A successive difference-of-convex approximation method for a class of nonconvex nonsmooth optimization problems, Valencia, July 8-11, 2018.

7. ISMP2018. A successive difference-of-convex approximation method for a class of nonconvex nonsmooth optimization problems, Bordeaux, July 1-6, 2018.

8. SIAM-ALA18. An exact penalty method for semidefinite-box constrained low-rank matrix optimization problems, Hong Kong, May 4-8, 2018.

9. OP17. Further properties of the forward-backward envelope with applications to difference-of-convex programming, Vancouver, May 22-25, 2017.

Visits

1. June 2014 - June 2015, The Hong Kong Polytechnic University, hosted by Professor Xiaojun Chen.

Links

My link in Google Scholar.