Qing Liu
Qing Liu's Chinese name

Qing Liu



Pattern Recognition and Intelligent System,
School Computer Science and Engineering,
Nanjing University of Science and Technology,
200 Xiaolingwei, Nanjing, 210094, China.
Laboratory: Room 4053, Computer Science Building,
Nanjing University of Science and Technology
URL: http://www.patternrecognition.cn/~liuqing
Email: clyqig2008@126.com


Currently I am a second year phd candidate of the School of Computer Science and Engineering in Nanjing University of Science and Technology and a member of Pattern Recognition Group at NUST. I received my B.Sc. and M.E. degree in School of Mathematics in Inner Mongolia University in June 2009 and school of computer science in Jiangsu University in June 2013 respectively.

Research Interests

1. Particle Swarm Optimization
2. Low-Rank Matrix Completion
3. Neural Network


[1] Qing Liu, Zhihui Lai, Zongwei Zhou and Zhong Jin. ˇ°A truncated nuclear norm regularization method based on weighted residual error for matrix completionˇ±, IEEE Trans. on Image Processing,Vol.25, Issue 1, pp. 316-330,2016.
[2] Qing Liu, Fei Han, ˇ°A Hybrid Attractive and Repulsive Particle Swarm Optimization Based on gradient Searchˇ±, in Proceedings of the 9th international conference on Intelligent Computing Theories and Technology, vol. 7996, pp. 155-162, 2013.
[3] Qing Liu, Franck Darvoine, Jian Yang and Zhong Jin, ˇ°A L_(2,1) Norm Minimization Method based on Qatar Riyal Decomposition for Fast Matrix Completionˇ±, IEEE Trans. on Neural Networks and Learning Systems (TNNLS), Feb. 2017. Major Revision.
[4] Qing Liu, Ying Cui, Pei Yang and Zhong Jin, ˇ°A Matrix Bi-Factorization based Iteratively Reweighted L_(2,1) Norm minimization method for matrix completionˇ±, Submitted to IEEE Trans. on Image Processing (TIP), Sep. 2016.
[5] Fei Han, Qing Liu, ˇ°A diversity-guided hybrid particle swarm optimization based on gradient searchˇ±, Neurocomputing, vol. 137, pp. 234-240, 2014.
[6] Fei Han, Qing Liu, ˇ°A Diversity-Guided Hybrid Particle Swarm Optimizationˇ±, in Proceedings of the 8th International Conference on Intelligent Computing (ICIC), vol. 304, pp. 461-466, 2012.
[7] Fei Han and Qing Liu, ˇ°An Improved Hybrid PSO Based on ARPSO and the Quasi-Newton Methodˇ±, Lecture Notes in Computer Science, vol. 9140, pp. 460-467, 2015.

        Last modified on 2017-02-09.