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[2020]
1.Min Yang, Chengming Li, Qingyao Wu*, Zhou Zhao, Xiaojun Chen, Ying Shen, Hierarchical Human-like Deep Neural Networks for Abstractive Text Summarization, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2020
2.Yifan Zhang#, Ying Wei#, Qingyao Wu#, Peilin Zhao, Shuaicheng Niu, Junzhou Huang, Mingkui Tan, Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis, IEEE Transactions on Image Processing, 2020
3.Yifan Zhang#, Peilin Zhao#, Qingyao Wu#, Bin Li, Junzhou Huang, and Mingkui Tan, Cost-Sensitive Portfolio Selection via Deep Reinforcement Learning, IEEE Transactions on Knowledge and Data Engineering, DOI: 10.1109/TKDE.2020.2979700, 2020
4.Yifan Zhang, Peilin Zhao, Shuaicheng Niu, Jiezhang Cao, Junzhou Huang, Qingyao Wu#, Mingkui Tan, Online Adaptive Asymmetric Active Learning with Limited Budgets, IEEE Transactions on Knowledge and Data Engineering, DOI: 10.1109/TKDE.2019.2955078, 2020
5.Hanrui Wu; Yuguang Yan; Yuzhong Ye; Michael K Ng; Qingyao Wu*, Geometric Knowledge Embedding for Unsupervised Domain Adaptation, Knowledge-Based Systems, 191: 105155. 2020
6.Mingkui Tan, Yuguang Yan, Jiezhang Cao, Qingyao Wu*, Learning Sparse PCA with Stabilized ADMM Method on Stiefel Manifold, IEEE Transactions on Knowledge and Data Engineering, DOI: 10.1109/TKDE.2019.2935449, 2020
[2019]
1.Xiaojun Chen, Renjie Chen, Qingyao Wu*, Yixiang Fang, Feiping Nie, Zhexue Huang, LABIN: Balanced Min Cut for Large-scale Data, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 31(3), pp.725-739, 2019 (IF:7.982)
2.Runhao Zeng, Chuang Gan, Peihao Chen, Wenbing Huang, Qingyao Wu, Mingkui Tan, Breaking Winner-takes-all: Iterative-winners-out Networks for Weakly Supervised Temporal Action Localization, IEEE Transactions on Image Processing, 28(12): 5797-5808, 2019
3.Fan Lyu, Qi Wu, Fuyuan Hu, Qingyao Wu, Mingkui Tan, Attend and Imagine: Multi-label Image Classification with Visual Attention and Recurrent Neural Networks, IEEE Transactions on Multimedia, 21(8): 1971-1981, 2019
4.Hanrui Wu, Yuguang Yan, Michael Ng, Huaqing Min, Qingyao Wu*, Online Heterogeneous Transfer Learning by Knowledge Transition, ACM Transactions on Intelligent Systems and Technology, 10(3): 1-19, 2019
5.Xiaojun Chen, Joshua Z. Huang, Qingyao Wu*, Min Yang Subspace Weighting Co-Clustering of Gene Expression Data, IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 16(2), 352-364, April 2019 (IF: 2.896)
6.Chi Zhang, Guosheng Lin, Fayao Liu, Jiushuang Guo, Qingyao Wu, Rui Yao, Pyramid Graph Networks with Connection Attentions for Region-Based One-Shot Semantic Segmentation, ICCV 2019
7.Min Yang, Lei Chen, Xiaojun Chen, Qingyao Wu, Wei Zhou, Ying Shen, Knowledge-enhanced Hierarchical Attention for Community Question Answering with Multi-task and Adaptive Learning, IJCAI 2019
8.Shihao Zhang, Yuguang Yan, Pengshuai Yin, Zhen Qiu, Wei Zhao, Guiping Cao, Wan Chen, Jin Yuan, Risa Higashita, Qingyao Wu, Mingkui Tan, Jiang Liu. “Guided M-Net for High-resolution Biomedical Image Segmentation with Weak Boundaries and Noise. OMIA. 2019 (best paper)
9.Yifan Zhang, Hanbo Chen, Ying Wei, Peilin Zhao, Jiezhang Cao, Mingkui Tan, Qingyao Wu*, Xinjuan Fan, Xiaoying Lou, Hailing Liu, Jinlong Hou, Xiao Han, Jianhua Yao, Junzhou Huang, From Whole Slide Imaging to Microscopy: Deep Microscopy Adaptation Network for Histopathology Cancer Image Classification, MICCAI 2019
10.Shihao Zhang, Huazhu Fu, Yuguang Yan, Yubing Zhang, Qingyao Wu, Ming Yang, Mingkui Tan, Yanwu Xu, Attention Guided Network for Retinal Image Segmentation, MICCAI 2019
11.Pengshuai Ying#, Qingyao Wu#, Mingkui Tan, Ming Yang, Yubing Zhang, Huaqing Min, Yanwu Xu, PM-NET: Pyramid Multi-Label Network for Optic Disc and Cup Segmentation, MICCAI 2019
12.Yuguang Yan, Mingkui Tan, Yanwu Xu, Jiezhang Cao, Michael K. Ng, Huaqing Min, Qingyao Wu*, Oversampling for Imbalanced Data via Optimal Transport, Association for the Advancement of Artificial Intelligence (AAAI), 2019
[2018]
1.Yuguang Yan, Qingyao Wu*, Mingkui Tan*, Michael Ng, Huaqing Min, Ivor Tsang, Online Heterogeneous Transfer by Hedge Ensemble of Offline and Online Decisions, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 29(7), pp. 3252-3263, 2018 (IF:7.982)
2.Renjie Chen, Ning Sun, Xiaojun Chen, Min Yang and Qingyao Wu*,Supervised Feature Selection With a Stratified Feature Weighting Method, IEEE Access, 6: 15087-15098, 2018 (IF:3.557)
3.Zhuangwei Zhuang, Mingkui Tan, Bohan Zhuang, Jing Liu, Yong Guo, Qingyao Wu, Junzhou Huang, Jinhui Zhu Discrimination-aware Channel Pruning for Deep Neural Networks, Thirty-second Conference on Neural Information Processing Systems (NIPS), 2018
4.Junhong Huang, Mingkui Tan, Yuguang Yan, Chunmei Qing, Qingyao Wu, Zhuliang Yu, Dong Xu Cartoon-to-Photo Facial Translation with Generative Adversarial Networks, ACML, 2018
5.Jiezhang Cao#, Yong Guo#, Qingyao Wu#, Chunhua Shen, Mingkui Tan*, Adversarial Learning with Local Coordinate Coding, Proceedings of the 35th International Conference on Machine Learning (ICML 2018), 2018
6.Yifan Zhang, Peilin Zhao, Jiezhang Cao, Wenye Ma, Junzhou Huang, Qingyao Wu*, Mingkui Tan Online Adaptive Asymmetric Active Learning for Budgeted Imbalanced Data, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2018
7.Yuguang Yan, Wen Li, Hanrui Wu, Huaqing Min, Mingkui Tan*, Qingyao Wu*, Semi-Supervised Optimal Transport for Heterogeneous Domain Adaptation, Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), 2018
8.Chaorui Deng, Qi Wu, Qingyao Wu*, Fuyuan Hu, Fan Lyu, Mingkui Tan*, Visual Grounding via Accumulated Attention, In Proceeding of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018
9.Yong Guo#, Qingyao Wu#, Jian Chen, Mingkui Tan, Memorized Batch Normalization for Training Deep Neural Networks,Association for the Advancement of Artificial Intelligence (AAAI), 2018
10.Renjie Chen, Xiaojun Chen, Guowen Yuan, Wenya Sun and Qingyao Wu, A Stratified Feature Ranking Method for Supervised Feature Selection, Association for the Advancement of Artificial Intelligence (AAAI), 2018 (Student Abstract Paper)
[2017]
1.Qingyao Wu, Hanrui Wu, Xiaoming Zhou, Mingkui Tan, Yonghui Xu, Yuguang Yan, Tianyong Hao, Online Transfer Learning with Multiple Homogeneous or Heterogeneous Sources, IEEE Transactions on Knowledge and Data Engineering (TKDE), 29(7), pp.1494-1507, 2017 JULY (IF:3.857)
2.Xutao Li, Michael K. Ng, Gao Cong, Yunming Ye, and Qingyao Wu, MR-NTD: Manifold Regularization Nonnegative Tucker Decomposition for Tensor Data Dimension Reduction and Representation, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 28(8), 1787-1800, 2017 (IF: 7.982)
3.Yonghui Xu, Sinno Pan, Hui Xiong, Qingyao Wu, Yonghua Luo, Huaqing Min, Henjie Song, A Unified Framework for Metric Transfer Learning, IEEE Transactions on Knowledge and Data Engineering (TKDE), 29(6),1158-1171, 2017 JUNE (IF:3.857)
4.Qingyao Wu, Xiaoming Zhou, Yuguang Yan, Hanrui Wu, Huaqing Min, Online Transfer Learning by Leveraging Multiple Source Domains Knowledge and Information Systems, 52(3), pp 687-707, 2017, Sep (IF: 2.397)
5.Yonghui Xu, Huaqing Min, Qingyao Wu*, Henjie Song, Multi-Instance Metric Transfer Learning for Genome-Wide Protein Function Prediction, Scientific Reports, 7:41831, 2017 (IF: 4.011)
6.Tianyong Hao, Wenxiu Xie, Qingyao Wu, Heng Weng, Yingying Qu. Leveraging Question Target Word Features through Semantic Relation Expansion for Answer Type Classification. Knowledge-Based Systems. 133(1), pp.43-52, 2017 (IF: 5.101)
7.Jiezhang Cao#, Qingyao Wu#, Yuguang Yan, Li Wang, Mingkui Tan, On the Flatness of Loss Surface for Two-layered ReLU Networks, the 9th Asian Conference on Machine Learning (ACML), 545-560, 2017
8.Yuguang Yan, Wen Li, Michael Ng, Mingkui Tan, Hanrui Wu, Huaqing Min, Qingyao Wu*, Learning Discriminative Correlation Subspace for Heterogeneous Domain Adaptation, Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), 2017, 3252-3258
9.Chao Han#, Qingyao Wu#, Jiezhang Cao, Michael K. Ng, Mingkui Tan, Jian Chen, Tensor based Relations Ranking for Multi-relational Collective Classification, In Proceeding of IEEE Conference on Data Mining (ICDM), 2017 (# co-first authors)
10.Xiaojun Chen, Guowen Yuan, JianZhe Zhang, Joshua Zhexue Huang, Qingyao Wu, A Self-Balanced Min-Cut Algorithm for Image Clustering, IEEE International Conference on Computer Vision (ICCV), 2017
[2016]
1.Qingyao Wu, Mingkui Tan, Hengjie Song, Jian Chen, Michael K. Ng. ML-Forest: A Multi-label Tree Ensemble Method for Multi-Label Classification, IEEE Transactions on Knowledge and Data Engineering (TKDE), 28(10), 2016, Oct (IF:3.857)
2.Chao Han, Yunkun Tan, Jinhui Zhu, Yong Guo, Jian Chen, Qingyao Wu*, Online feature selection of Class Imbalance via PA algorithm Journal of Computer Science and Technology (JCST), 31(4): 673-682, 2016 (IF: 0.878)
3.Yonghui Xu, Huaqing Min, Hengjie Song and Qingyao Wu*, Multi-Instance Multi-Label Distance Metric Learning for Genome-Wide Protein Function Prediction, Computational Biology and Chemistry, 11(5):891-902, 2016 (IF: 1.412)
4.Michael K. Ng, Qingyao Wu, Chenyang Shen, A fast Markov chain based algorithm for MIML learning, Neurocomputing, 216 (5), 763-777, 2016 (IF:3.241)
5.Yuguang Yan, Qingyao Wu*, Mingkui Tan, Huaqing Min, Online Heterogeneous Transfer Learning by Weighted Offline and Online Classifiers, ECCV workshop on TASK Transferring and Adapting Source Knowledge in Computer Vision, 2016 (Honorable Mention Paper Award)
6.Feng Wu, Qiong Liu*, Tianyong Hao, Xiaojun Chen, and Qingyao Wu*, Online Multi-Instance Multi-Label Learning for Protein Function Prediction, IEEE BIBM, 780-785, 2016 Dec
7.Yongxin Liao, Shenxi Yuan, Jian Chen, Qingyao Wu* and Bin Li, Joint Classification with Heterogeneous labels using random walk with dynamic label propagation, V9651, pp 3-13, PAKDD, 2016 April
[2015]
1.Qingyao Wu*, Yunming Ye, Haijun Zhang, Tommy W.S.Chow, and Shen-Shyang Ho. ML-TREE: A Tree-Structure Based Approach to Multi-Label Learning, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 26(3): 430-443, 2015, Mar. (IF:6.108) (IF:7.982)
2.Qingyao Wu, Mingkui Tan, Xutao Li, Huaqing Min, Ning Sun*, NMFE-SSCC: Non-negative matrix factorization ensemble for semi-supervised collective classification, Knowledge-Based Systems, 89 (2015): 160-172. (IF: 5.101)
3.Qingyao Wu, Zhenyu Wang, Chunshan Li, Yunming Ye, Yueping Li, and Ning Sun. Protein functional properties prediction in sparsely-label PPI networks through Regularized non-negative matrix factorization, BMC Systems Biology, 9 (Suppl 1):S9, 2015 (IF:2.050)
4.Qingyao Wu, Jian Chen, Shen-Shyang Ho, Xutao Li, Huaqing Min, Chao Han, Multi-Label Regularized Generative Model for Semi-Supervised Collective Classification in Large-Scale Networks, Big Data Research, 2 (4), 187-201, 2015
5.Chao Han, Jian Chen, Qingyao Wu*, Shuai Mu, Huaqing Min, Sparse Markov Chain based Semi-Supervised Multi-Instance Multi-Label Method for Protein Function Prediction, Journal of Bioinformatics and Computational Biology (JBCB), 13(05), 2015. (IF: 0.991)
6.Thanh-Tung Nguyen, Joshua Z. Huang, Qingyao Wu, Thuy T. Nguyen and Mark J. Li. Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests BMC Genomics, 16(Suppl 2):S5, 2015 (IF: 3.730)
[2014, 2013, 2012]
1.Qingyao Wu, Michael Ng, and Yunming Ye. Co-Transfer Learning Using Coupled Markov Chains with Restart, IEEE Intelligent Systems, 29(4), pp.26-33, 2014 (IF:4.464)
2.Qingyao Wu, Michael Ng, Yunming Ye, Xutao Li, and Yan Li. Multi-Label Collective Classification via Markov Chain Based Learning Method, Knowledge-Based Systems, 63: 1-14, 2014 (IF: 5.101)
3.Qingyao Wu*, Yunming Ye, Haijun Zhang, Michael Ng, Xutao Li, Shen-Shyang Ho. ForesTexter: An Efficient Random Forest Algorithm for Imbalanced Text Categorization, Knowledge-Based Systems, 67: 105-116, 2014 (IF:5.101)
4.Qingyao Wu, Yunming Ye, Shen-Shyang Ho and Shuigeng Zhou. Semi-Supervised Multi-label Collective Classification Ensemble for Functional Genomics, BMC Genomics, 15 (Suppl 9):S17, 2014 (IF:3.730)
5.Qingyao Wu, Yunming Ye, Michael Ng, Shen-Shyang Ho and Ruichao Shi. Collective prediction of protein functions from protein-protein interaction networks, BMC Bioinformatics, 15(S9), no. Suppl 2, 2014 (IF:2.213)
6.Ruichao Shi, Qingyao Wu*, Yunming Ye, and Shen-Shyang Ho. A Generative Model with Network Regularization for Semi-Supervised Collective Classification, SDM, 2014
7.Qingyao Wu, Michael Ng, and Yunming Ye. Markov-MIML: A Markov Chain Based Multi-Instance Multi-Label Learning Algorithm, Knowledge and Information Systems, 37(1): 83-104, 2013 (IF:2. 397)
8.Xutao Li, Yunming Ye, Michael Ng and Qingyao Wu*. MultiFacTV: Module Detection from Higher-order Time Series Biological Data, BMC Genomics, 14(S4), 2013 (IF: 3.730)
9.Yunming Ye, Qingyao Wu, Joshua Zhexue Huang, Michael K. Ng and Xutao Li. Stratified Sampling for Feature Subspace Selection in Random Forest for High Dimensional Data, Pattern Recognition (PR), 46(3): 769-787, 2013 (IF:3.962)
10.Yunming Ye, Qingyao Wu, K.P.Chow, Lucas C.K. Hui, and S.M. Yiu. Unknown Chinese Word Extraction based on Variety of Overlapping Strings, Information Processing and Management (IPM), 49(2): 497-512, 2013 (IF:3.444)
11.Qingyao Wu, Yunming Ye, Xiaofeng Zhang and Shen-Shyang Ho. Cluster Tree based Multi-Label Classification for Protein Function Prediction. IEEE BIBM-2013
12.Qingyao Wu, Yunming Ye, Yang Liu, and Michael K. Ng. SNP Selection and Classification of Genome-wide SNP Data Using Stratified Sampling Random Forests, IEEE Transactions on Nanobioscience, 11(3), 216-227, 2012 (IF:1.927)
13.Michael Ng, Qingyao Wu and Yunming Ye. Co-Transfer Learning via Joint Transition Probability Graph Based Method. SIGKDD Workshop on CDKD, pp.1-9, 2012 (Selected Best Paper to IEEE IS Special Issue)
14.Qingyao Wu, Yunming Ye, Yang Liu, and Michael Ng. Stratified Random Forest for Genome-wide Association Study, IEEE BIBM, pp.10-15, 2011
15.Xutao Li, Yunming Ye, Qingyao Wu and Michael Ng. MultiFacTV: Finding Modules from Higher-order Gene Expression Profiles with Time Dimension, IEEE BIBM, pp. 53-58, 2012
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