Mingkui Tan - Google Scholar Citations

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	All	Since 2015
Citations	1714	1478
h-index	21	21
i10-index	38	37

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Co-authors

Ivor W. TsangResearch Director & Professor of AI, Centre for AI, University of Technology SydneyVerified email at uts.edu.au
Li WangUniversity of Texas at ArlingtonVerified email at uta.edu
Professor Javen Qinfeng Shi 史勤峰Director and Founder, Probabilistic Graphical Model Group, Professor of University of AdelaideVerified email at adelaide.edu.au
Anton van den HengelProfessor of Machine Learning, University of AdelaideVerified email at adelaide.edu.au
Shutao Li (李树涛)College of Electrical and Information Engineering, Hunan University (湖南大学电气与信息工程学院)Verified email at hnu.edu.cn
Chunhua ShenSchool of Computer Science, The University of AdelaideVerified email at adelaide.edu.au
Dong Xu, IEEE Fellow, Chair in Comp...University of SydneyVerified email at sydney.edu.au
Sinno Jialin PanNanyang Technological University, SingaporeVerified email at ntu.edu.sg
Professor Junbin GaoDiscipline of Business Analytics in Business School, The University of SydneyVerified email at sydney.edu.au
James T. KwokProfessor of Computer Science and Engineering, Hong Kong University of Science and TechnologyVerified email at cse.ust.hk
Bart VandereyckenAssociate Professor, University of GenevaVerified email at unige.ch
Zhen ZhangVerified email at mail.nwpu.edu.cn
Yew-Soon OngProfessor of Computer Science, IEEE FellowVerified email at ntu.edu.sg
Tat-Jen ChamNanyang Technological UniversityVerified email at ntu.edu.sg
Marcus ChenVerified email at alumni.stanford.edu
Yan Yanthe University of Iowa
Yi YangUniversity of Technology SydneyVerified email at uts.edu.au
Li WangUniversity of WashingtonVerified email at vcu.edu

Mingkui Tan

South China University of Technology

Verified email at scut.edu.cn - Homepage

Artificial Intelligence Machine Learning Large-scale Optimization


Title	Cited by	Year
Learning sparse svm for feature selection on very high dimensional datasets M Tan, L Wang, IW Tsang	183	2010
Gene selection using hybrid particle swarm optimization and genetic algorithm S Li, X Wu, M Tan Soft Computing 12 (11), 1039-1048, 2008	147	2008
Towards ultrahigh dimensional feature selection for big data M Tan, IW Tsang, L Wang Journal of Machine Learning Research, 2014	142	2014
Heterogeneous domain adaptation for multiple classes JT Zhou, IW Tsang, SJ Pan, M Tan Artificial intelligence and statistics, 1095-1103, 2014	95	2014
A hybrid PSO-BFGS strategy for global optimization of multimodal functions S Li, M Tan, IW Tsang, JTY Kwok IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 41 …, 2011	79	2011
Discrimination-aware channel pruning for deep neural networks Z Zhuang, M Tan, B Zhuang, J Liu, Y Guo, Q Wu, J Huang, J Zhu Advances in Neural Information Processing Systems, 875-886, 2018	70	2018
Robust kernel low-rank representation S Xiao, M Tan, D Xu, ZY Dong IEEE transactions on neural networks and learning systems 27 (11), 2268-2281, 2015	68	2015
Weighted block-sparse low rank representation for face clustering in videos S Xiao, M Tan, D Xu European Conference on Computer Vision, 123-138, 2014	63	2014
Tuning SVM parameters by using a hybrid CLPSO–BFGS algorithm S Li, M Tan Neurocomputing 73 (10-12), 2089-2096, 2010	53	2010
Riemannian pursuit for big matrix recovery M Tan, IW Tsang, L Wang, B Vandereycken, SJ Pan International Conference on Machine Learning, 1539-1547, 2014	47	2014
Towards effective low-bitwidth convolutional neural networks B Zhuang, C Shen, M Tan, L Liu, I Reid Proceedings of the IEEE conference on computer vision and pattern …, 2018	46	2018
Blind image deconvolution by automatic gradient activation D Gong, M Tan, Y Zhang, A Van den Hengel, Q Shi Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016	45	2016
ML-FOREST: A multi-label tree ensemble method for multi-label classification Q Wu, M Tan, H Song, J Chen, MK Ng IEEE transactions on knowledge and data engineering 28 (10), 2665-2680, 2016	41	2016
Compressive representation for device-free activity recognition with passive RFID signal strength L Yao, QZ Sheng, X Li, T Gu, M Tan, X Wang, S Wang, W Ruan IEEE Transactions on Mobile Computing 17 (2), 293-306, 2017	33	2017
Learning graph structure for multi-label image classification via clique generation M Tan, Q Shi, A van den Hengel, C Shen, J Gao, F Hu, Z Zhang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015	33	2015
Matching pursuit LASSO part I: Sparse recovery over big dictionary M Tan, IW Tsang, L Wang IEEE Transactions on Signal Processing 63 (3), 727-741, 2014	31	2014
Visual grounding via accumulated attention C Deng, Q Wu, Q Wu, F Hu, F Lyu, M Tan Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018	30	2018
Minimax sparse logistic regression for very high-dimensional feature selection M Tan, IW Tsang, L Wang IEEE Transactions on Neural Networks and Learning Systems 24 (10), 1609-1622, 2013	30	2013
Online transfer learning with multiple homogeneous or heterogeneous sources Q Wu, H Wu, X Zhou, M Tan, Y Xu, Y Yan, T Hao IEEE Transactions on Knowledge and Data Engineering 29 (7), 1494-1507, 2017	26	2017
Fast algorithms for linear and kernel svm+ W Li, D Dai, M Tan, D Xu, L Van Gool Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016	26	2016

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