About me

  I am currently a professor with the School of Software Engineering at South China University of Technology. I received my Bachelor Degree in Environmental Science and Engineering in 2006 and Master degree in Control Science and Engineering in 2009, both from Hunan University in Changsha, China. I received the Ph.D. degree in Computer Science from Nanyang Technological University, Singapore, in 2014. From 2014-2016, I worked as a Senior Research Associate on computer vision in the School of Computer Science, University of Adelaide, Australia. My research interests include machine learning, sparse analysis, deep learning and large-scale optimization.


NAT: Neural Architecture Transformer for Accurate and Compact Architectures

Yong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Jian Chen, Peilin Zhao, Junzhou Huang

NeurIPS 2019

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Multi-marginal Wasserstein Gan

Jiezhang Cao, Langyuan Mo, Yifan Zhang, Kui Jia, Chunhua Shen, Mingkui Tan

NeurIPS 2019

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Guided M-Net for High-Resolution Biomedical Image Segmentation with Weak Boundaries

Shihao Zhang, Yuguang Yan, Pengshuai Yin, Zhen Qiu, Wei Zhao, Guiping Cao, Wan Chen, Jin Yuan, Risa Higashita, Qingyao Wu, Mingkui Tan, Jiang Liu


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Discrimination-aware Channel Pruning for Deep Neural Networks

Zhuang Zhuangwei, Tan Mingkui, Zhuang Bohan, Liu Jing, Guo Yong, Wu Qingyao, Huang Junzhou, Zhu Jinhui

NeurIPS 2018

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Visual Grounding via Accumulated Attention

Chaorui Deng, Qi Wu, Qingyao Wu, Fuyuan Hu, Fan Lyu, Mingkui Tan

CVPR 2018

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Improving Generative Adversarial Networks with Local Coordinate Coding

Jiezhang Cao, Yong Guo, Qingyao Wu, Chunhua Shen, Junzhou Huang, Mingkui Tan

TPAMI 2020

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Visual Grounding via Accumulated Attention

Chaorui Deng, Qi Wu, Qingyao Wu, Fuyuan Hu, Fan Lyu, Mingkui Tan

IEEE Transactions on Pattern Analysis and Machine Intelligence 2020

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Breaking Winner-Takes-All: Iterative-Winners-Out Networks for Weakly Supervised Temporal Action Localization

Runhao Zeng, Chuang Gan, Peihao Chen, Wenbing Huang, Qingyao Wu, Mingkui Tan

IEEE Trans. Image Processing 28(12) 2019

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Attend and Imagine: Multi-Label Image Classification With Visual Attention and Recurrent Neural Networks

Fan Lyu, Qi Wu, Fuyuan Hu, Qingyao Wu, Mingkui Tan

IEEE Trans. Multimedia 21(8) 2019

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Towards ultrahigh dimensional feature selection for big data

Mingkui Tan, Ivor W. Tsang, Li Wang

Journal of Machine Learning Research 15(1) 2014

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Preprint Paper

Structured Binary Neural Networks for Image Recognition

Bohan Zhuang, Chunhua Shen, Mingkui Tan, Lingqiao Liu, Ian Reid

CoRR abs/1909.09934 2019

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Graph Convolutional Networks for Temporal Action Localization

Runhao Zeng, Wenbing Huang, Mingkui Tan, Yu Rong, Peilin Zhao, Junzhou Huang, Chuang Gan

CoRR abs/1909.03252 2019

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Effective Training of Convolutional Neural Networks with Low-bitwidth Weights and Activations

Bohan Zhuang, Jing Liu, Mingkui Tan, Lingqiao Liu, Ian Reid, Chunhua Shen

CoRR abs/1908.04680 2019

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Training Quantized Network with Auxiliary Gradient Module

Bohan Zhuang, Lingqiao Liu, Mingkui Tan, Chunhua Shen, Ian Reid

CoRR abs/1903.11236 2019

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Continual Reinforcement Learning with Diversity Exploration and Adversarial Self-Correction

Fengda Zhu, Xiaojun Chang, Runhao Zeng, Mingkui Tan

CoRR abs/1906.09205 2019

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Dual Reconstruction Nets for Image Super-Resolution with Gradient Sensitive Loss

Yong Guo, Qi Chen, Jian Chen, Junzhou Huang, Yanwu Xu, Jiezhang Cao, Peilin Zhao, Mingkui Tan

CoRR abs/1809.07099 2018

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The Shallow End: Empowering Shallower Deep-Convolutional Networks through Auxiliary Outputs

Yong Guo, Mingkui Tan, Qingyao Wu, Jian Chen, Anton Van Den Hengel, Qinfeng Shi

CoRR abs/1611.01773 2017

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Scalable Nuclear-norm Minimization by Subspace Pursuit Proximal Riemannian Gradient

Mingkui Tan, Shijie Xiao, Junbin Gao, Dong Xu, Anton Van Den Hengel, Qinfeng Shi

CoRR abs/1503.02828 2015

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