Mingkui Tan - Google Scholar

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	All	Since 2015
Citations	2341	2097
h-index	26	26
i10-index	54	53

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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 HengelDirector, Australian Institute for Machine Learning, UoA | Director of Applied Science, AmazonVerified email at adelaide.edu.au
Chunhua ShenSchool of Computer Science, The 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
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
Yi YangUniversity of Technology SydneyVerified email at uts.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 ZhangThe University of AdelaideVerified email at adelaide.edu.au
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
Li WangUniversity of WashingtonVerified email at vcu.edu

Mingkui Tan

South China University of Technology

Verified email at scut.edu.cn - Homepage

Machine Learning Large-scale Optimization


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Learning sparse svm for feature selection on very high dimensional datasets M Tan, L Wang, IW Tsang ICML, 2010	192	2010
Towards ultrahigh dimensional feature selection for big data M Tan, IW Tsang, L Wang Journal of Machine Learning Research, 2014	155	2014
Gene selection using hybrid particle swarm optimization and genetic algorithm S Li, X Wu, M Tan Soft Computing 12 (11), 1039-1048, 2008	151	2008
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	144	2018
Heterogeneous domain adaptation for multiple classes JT Zhou, IW Tsang, SJ Pan, M Tan Artificial intelligence and statistics, 1095-1103, 2014	107	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	84	2011
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	77	2015
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	75	2018
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	71	2014
Tuning SVM parameters by using a hybrid CLPSO–BFGS algorithm S Li, M Tan Neurocomputing 73 (10-12), 2089-2096, 2010	55	2010
Deep high-resolution representation learning for visual recognition J Wang, K Sun, T Cheng, B Jiang, C Deng, Y Zhao, D Liu, Y Mu, M Tan, ... IEEE transactions on pattern analysis and machine intelligence, 2020	52	2020
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	51	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	50	2016
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	49	2018
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	49	2017
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
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	39	2015
Structured binary neural networks for accurate image classification and semantic segmentation B Zhuang, C Shen, M Tan, L Liu, I Reid Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019	37	2019
Domain-symmetric networks for adversarial domain adaptation Y Zhang, H Tang, K Jia, M Tan Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019	36	2019
T-c3d: Temporal convolutional 3d network for real-time action recognition K Liu, W Liu, C Gan, M Tan, H Ma Thirty-second AAAI conference on artificial intelligence, 2018	34	2018

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