个人简介
吴庆耀，华南理工大学软件学院教授、博士生导师，国家级青年人才项目入选者；大数据与智能机器人教育部重点实验室副主任，广州市机器人软件及复杂信息处理重点实验室主任，深度学习与机器视觉等三个校企联合实验室主任；Elsevier期刊Software Impacts副主编、IEEE 电子商务工程国际会议 2021年大会主席及2022年/2023年程序主席，入选2022年美国斯坦福大学发布的全球前2%顶尖科学家榜单；主持三项国家自然科学基金与广东省重点领域研发计划和广东省特支计划项目。获授权国内发明专利10余项、PCT国际专利3项；主要从事计算机视觉、数据挖掘、机器人调度决策、多模态金融数据分析理论与应用研究，相关成果发表于CVPR、ICCV、IJCAI、AAAI和TKDE、TNNLS、TIP等CCF-A类会议和期刊。曾获2018年度广东省自然科学奖二等奖、2016年度深圳市自然科学奖二等奖。
学历
2009.09–2013.12，哈尔滨工业大学（深圳），计算机软件与理论，博士 （导师：叶允明）
2007.09–2009.09，哈尔滨工业大学（深圳），计算机科学与技术，硕士 （导师：叶允明）
2003.09–2007.09，华南理工大学，软件工程，学士（导师：闵华清）
教学经历
主讲课程：《机器学习》《IT项目管理》等本科生课程；《高级机器学习》等研究生课程。
工作经历
2018.9-至今，华南理工大学，软件学院，教授
2015.1-2018.8，华南理工大学，软件学院，副教授
社会兼职
担任国际期刊Software Impacts副主编；IEEE电子商务工程国际会议ICEBE 2021年大会主席ICEBE 2022年2023年程序主席；NeurIPS、ICML、CVPR、ICCV、ECCV等多个国际会议审稿人；TPAMI、TNNLS、TKDE等多个IEEE Trans.期刊审稿人。
研究方向
主要从事计算机视觉、数据挖掘、机器人调度决策、多模态金融数据分析理论与应用研究
(1) 计算机视觉：图像与视频理解、AIGC、三维重建
(2) 数据挖掘：迁移学习、小样本学习、异常欺诈检测
(3) 机器人调度决策：多任务调度、定位与建图、路径规划
(4) 多模态金融数据分析：多模态投资组合策略
获奖情况
(1) 2022年，美国斯坦福大学发布的全球2%顶尖科学家
(2) 2021年，广东省课程思政改革示范课程奖
(3) 2019年，“广东特支计划”科技创新青年拔尖
(4) 2018年，广东省自然科学奖二等奖
(5) 2018年，广东省计算机学会优秀论文奖一等奖
(6) 2017年，广州市珠江科技新星
(7) 2017年，CCF-腾讯犀牛鸟基金优秀奖
(8) 2016年，深圳市自然科学奖二等奖
(9) 2016年，ECCV 会议Transferring and Adapting Source Knowledge in Computer Vision研讨会荣誉论文奖
科研项目
主持国家级和省部级重大项目等共20多项
(1) 广州诺顶智能科技有限公司-华南理工大学芯片半导体人工智能联合实验室，2024-2027
(2) 国家自然科学基金面上基金，“基于3D骨架自监督学习的视频动作表示学习研究”，2023-2026
(3) 广东省自然科学基金-面上项目，“面向视频动作识别的3D骨架自监督学习研究”， 2023-2024
(4) 华南理工大学—深圳金三立视频科技有限公司深度学习与机器视觉联合实验室，2021-2024
(5) 华南理工大学—广州易方信息科技有限公司智能音视频联合实验室，2021-2024
(6) 中邮消费金融公司与华南理工大学（软件学院）校企合作，语音去躁与识别，2022-2022
(7) 腾讯犀牛鸟基金项目，面向异常用户标签挖掘的小样本学习技术研究，2022-2023
(8) 琶洲实验室青年学者项目，迁移学习关键技术研究与应用，2021-2023
(9) 广东省气象中心合作项目，对流系统演变特征分类与识别的人工智能算法，2021-2022
(10) “广东特支计划”科技创新青年拔尖人才，迁移学习关键技术研究，2020-2023
(11) 广东省重点研发项目，“多模态智能机器人视觉感知与人机交互关键技术研究及应用示范”，2018-2021
(12) 国家自然科学基金面上基金，“基于对抗表示学习的知识迁移关键技术研究”2019-2022
(13) 广州市珠江新星项目，“面向迁移学习的生成对抗网络研究”，2018-2021
(14) 国家自然科学基金青年基金，“基于概率语义分析的多关系图多类标分类方法研究”，2016-2018
(15) 广东省科技专项--公益研究与能力建设，“面向特定主题网络媒体大数据的深度学习技术研究及应用”，2017-2018
(16) 广东省科技专项--协同创新与平台环境建设，“深度形体动作识别关键技术研究及在社区安防上的应用”，2017-2018
(17) CCF-腾讯犀牛鸟基金项目，“面向广告推荐的深度学习模型压缩与特征理解及在小样本条件下的应用”，2019-2020
(18) CCF-腾讯犀牛鸟基金项目，“面向迁移学习的生成对抗网络研究及应用”，2017-2018
(19) 广东省教育厅青年创新人才，2016-2017
(20) 中央高校基本科研业务杰青项目，2015-2016
发表论文
以第一作者/通讯作者的身份在CVPR、ICCV、IJCAI、AAAI等会议和IEEE TKDE、IEEE TIP、IEEE TNNLS等期刊发表论文100多篇（*代表通讯作者 #代表共同一作）
[2024]
1. Ruirui Liu, Haoxian Liu, Huichou Huang, Bo Song, Qingyao Wu*, "Multimodal Multiscale Dynamic Graph Convolution Networks for Stock Price Movement Prediction", Pattern Recognition, 2024
2. Yukun Su, Yiwen Cao, Jingliang Deng, Fengyun Rao, Qingyao Wu*, "Spatial-Semantic Collaborative Cropping for User Generated Content", Association for the Advancement of Artificial Intelligence (AAAI), 2024
3. Xiaofeng Yang, Fayao Liu, Yi Xu, Hanjing Su, Qingyao Wu, Guosheng Lin, "Diverse and Stable 2D Diffusion Guided Text to 3D Generation with Noise Recalibration", Association for the Advancement of Artificial Intelligence (AAAI), 2024
4. Chaowei Fang, ziyin zhou, Junye Chen, Hanjing Su, Qingyao Wu, Guanbin Li, "Variance-insensitive and Target-preserving Mask Refinement for Interactive Image Segmentation", Association for the Advancement of Artificial Intelligence (AAAI), 2024
5. Yiwen Cao, Yukun Su, Jingliang Deng, Yu Zhang, Qingyao Wu*, "Adaptive Locally-Aligned Transformer for Low-Light Video Enhancement", Computer Vision and Image Understanding, 2024
[2023]
1. Hao Yun#, Yukun Su#, Guosheng Lin, Hanjing Su, Qingyao Wu*, "Contrastive Generative Network with Recursive-Loop for 3D Point Cloud Generalized Zero-Shot Classiffcation", Pattern Recognition, 2023, 144: 109843. 影响因子8，JCR一区，CCF B类期刊
2. Lvlong Lai#, Jian Chen#, Qingyao Wu*, "Zero-Shot Single-View Point Cloud Reconstruction via Cross-Category Knowledge Transferring", IEEE Transactions on Multimedia, 2023 (Early Access), DOI: 10.1109/TMM.2023.3282467. 影响因子7.3，JCR一区，CCF B类期刊
3. Yukun Su, Jingliang Deng, Ruizhou Sun, Guosheng Lin*, Hanjing Su, Qingyao Wu*, "A Unified Transformer Framework for Group-based Segmentation: Co-Segmentation, Co-Saliency Detection and Video Salient Object Detection", IEEE Transactions on Multimedia, 2023 DOI: 10.1109/TMM.2023.3264883. 影响因子7.3，JCR一区，CCF B类期刊
4. Ruizhou Sun#, Yukun Su#, Qingyao Wu*, "DENet: Disentangled Embedding Network for Visible Watermark Removal", Association for the Advancement of Artificial Intelligence (AAAI), 2023, 37(2): 2411-2419. CCF A类会议
5. Siraj Khan, Muhammad Asim*, Salabat Khan, Ahmad Musyafa, Qingyao Wu*, "Unsupervised domain adaptation using fuzzy rules and stochastic hierarchical convolutional neural networks", Computers and Electrical Engineering, 2023, 105: 108547. 影响因子4.3，JCR二区
6. Wenjun Wang, Qingyao Wu*, Chunshan Li*, "iEnhancer-DCSA: identifying enhancers via dual-scale convolution and spatial attention", BMC Genomics, 2023, 24(1): 393. 影响因子4.4，JCR一区
[2022]
1. Yukun Su，Guosheng Lin，Ruizhou Sun，Qingyao Wu*, General Object Pose Transformation Network from Unpaired Data, European Conference on Computer Vision (ECCV), 2022
2. Hanrui Wu, Yuguang Yan, Guosheng Lin, Min Yang, Michael K. Ng, Qingyao Wu*, "Iterative Refinement for Multi-source Visual Domain Adaptation"，IEEE Transactions on Knowledge and Data Engineering, 6, 2810-2823, 2022
3. Jiezhang Cao, Yong Guo, Qingyao Wu, Chunhua Shen, Junzhou Huang, Mingkui Tan, "Improving Generative Adversarial Networks with Local Coordinate Coding", IEEE Transactions on Pattern Analysis and Machine Intelligence, 44 (1) , pp.211-227, 2022
4. Chaorui Deng, Qi Wu, Qingyao Wu, Fan Lyu, Fuyuan Hu, Mingkui Tan, "Visual Grounding via Accumulated Attention" IEEE Transactions on Pattern Analysis and Machine Intelligence, 44 (3) , pp.1670-1684, 2022
5. Pengshuai Yin, Hongmin Cai, Qingyao Wu*, DF-Net:Deep Fusion Network for Multi-source Vessel Segmentation, Information Fusion, 78: 199-208, 2022
6. 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, 34 (1) , pp.236-248, 2022
7. Yukun Su, Yiwen Cao, Guosheng Lin, Qingyao Wu*, "Self-Supervised Object Localization with Joint Graph Partition", Association for the Advancement of Artificial Intelligence (AAAI), 2022
8. Haonan Luo, Guosheng Lin, Yazhou Yao, Zhenmin Tang, Qingyao Wu, and Xiansheng Hua, "Dense Semantics-Assisted Networks For Video Action Recognition." IEEE Transactions on Circuits and Systems for Video Technology, 5,3072-3084, 2022
9. Junyu Su, Yukun Su, Yu Zhang, Weiqiang Yang, Huichou Huang, Qingyao Wu*, "EpNet: Power lines foreign object detection with Edge Proposal Network and data composition", Knowledge-Based Systems, 249: 108857. 2022
10. Chao Han, Jian Chen, Mingkui Tan, Michael K. Ng, Qingyao Wu*, "A Tensor-based Markov Chain Model for Heterogeneous Information Network Collective Classification", IEEE Transactions on Knowledge and Data Engineering, 34(9): 4063-4076 (2022)
[2021]
1. Yukun Su, Guosheng Lin, Qingyao Wu*, Self-supervised 3D Skeleton Action Representation Learning with Motion Consistency and Continuity, In Proceedings of the IEEE/CVF Conference on Computer Vision(ICCV), 2021, pp. 13328-13338.
2. Yukun Su, Ruizhou Sun, Guosheng Lin, Qingyao Wu*, Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation, In Proceedings of the IEEE/CVF International Conference on Computer Vision(ICCV), 2021, (pp. 7004-7014)
3. Yukun Su, Guosheng Lin, Yun Hao, Qingyao Wu*, Modeling the Uncertainty for Self-supervised 3D Skeleton Action Representation Learning, In Proceedings of the 29th ACM International Conference on Multimedia , 2021 Oct 17 (pp. 769-778)
4. Xiaojin Zhong, Zhonghua Wu, Guosheng Lin, Qingyao Wu*, MV-TON: Memory-based Video Virtual Try-on network, In Proceedings of the 29th ACM International Conference on Multimedia , 2021, (pp. 908-916)
5. Minli Li, Peilin Zhao, Yifan Zhang, Shuaicheng Niu, Qingyao Wu#, Mingkui Tan, Structure-aware Mathematical Expression Recognition with Sequence-Level Modeling, ACM MM, 2021
6. Jiachun Wang, Fajie Yuan, Jian Chen*, Qingyao Wu*, Min Yang*, Yang Sun, Guoxiao Zhang, StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking, SIGIR, 2021
7. Xiaojun Chen, Yuzhong Ye, Qingyao Wu*, Feiping Nie, Fast Manifold Ranking with Local Bipartite Graph, IEEE Transactions on Image Processing, 30 (2021): 6744-6756.
8. Pengshuai Yin, Yanwu Xu, Jinhui Zhu, Changan Yi, Huichou Huang, Qingyao Wu*, Deep Level Set Learning for Optic Disc and Cup Segmentation, Neurocomputing, 464 , pp.330-341, 2021
9. Yuguang Yan, Hanrui Wu, Yuzhong Ye, Chaoyang Bi, Min Lu, Dapeng Liu, Qingyao Wu*, Michael K. Ng, "Transferable Feature Selection for Unsupervised Domain Adaptation", IEEE Transactions on Knowledge and Data Engineering, 34.11, 5536-5551, 2021.
10. Xiaojun Chen, Renjie Chen, Qingyao Wu*, Feiping Nie, Min Yang, "Semi-supervised Feature Selection via Structured Manifold Learning", IEEE Transactions on Cybernetics, 2168-2267, 2021
11. Hanrui Wu, Yuguang Yan, Sentao Chen, Xiangkang Huang, Qingyao Wu, Michael K. Ng, "Joint Visual and Semantic Optimization for zero-shot learning"， Knowledge-Based Systems, 215, 0950-7051, 2021
12. Pengshuai Yin, Jiayong Ye, Guoshen Lin, and Qingyao Wu*, "Graph Neural Network for 6D Object Pose Estimation", Knowledge-Based Systems, 218:106839, 2021
13. Zheng Xie, Zhiquan Wen, Yaowei Wang, Qingyao Wu*, Mingkui Tan, "Towards effective deep transfer via attentive feature alignment", Neural Networks, 138, pp.98-109, 2021
14. Hanrui Wu, Qingyao Wu, Michael K. Ng, “Knowledge Preserving and Distribution Alignment for Heterogeneous Domain Adaptation”, ACM Transactions on Information Systems, 40(1), 1-29, 2021
15. Chi Zhang, Guankai Li, Guosheng Lin, Qingyao Wu, Rui Yao, “CycleSegNet: Object Co-Segmentation With Cycle Refinement and Region Correspondence”, IEEE Transactions on Image Processing, 30, 1057-7149, 2021
16. Weichan Zhong, Xiaojun Chen, Qingyao Wu, Min Yang, and Joshua Z. Huang, Selection of diverse features with a diverse regularization, Pattern Recogniton, 120, 108154 , 2021
17. Mingkui Tan, Zhibin Hu, Yuguang Yan, Jiezhang Cao, Dong Gong, Qingyao Wu*, "Learning Sparse PCA with Stabilized ADMM Method on Stiefel Manifold", IEEE Transactions on Knowledge and Data Engineering, 33(3), 1078-1088, 2021
18. Yifan Zhang, Peilin Zhao, Shuaicheng Niu, Qingyao Wu#, Jiezhang Cao, Junzhou Huang, Mingkui Tan, "Online Adaptive Asymmetric Active Learning with Limited Budgets", IEEE Transactions on Knowledge and Data Engineering, 33(6), 1041-4347, 2021
[2020]
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, 2020 (IF:8.793)
2. Min Yang, Chengming Li, Ying Shen, 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), 32(6), 2744-2757, 2020
3. Min Yang, Junhao Liu, Ying Shen, Zhou Zhao, Xiaojun Chen, Qingyao Wu*, Chengming Li, "An Ensemble of Generation- and Retrieval-Based Image Captioning With Dual Generator Generative Adversarial Network" IEEE Transactions on Image Processing, 29, 9627-9640, 2020
4. Hanrui Wu, Yuguang Yan, Michael K. Ng, Qingyao Wu*, "Domain-attention Conditional Wasserstein Distance for Multi-source Domain Adaptation", ACM Transactions on Intelligent Systems and Technology, 11(4),1-19, 2020
5. Yukun Su, Guosheng Lin, Jinhui Zhu, Qingyao Wu*, "Human interaction learning on 3D skeleton point clouds for video violence recognition", In European Conference on Computer Vision, pp. 74-90. Springer, Cham, 2020
6. Lichang Chen, Guosheng Lin, Shijie Wang, Qingyao Wu, "Graph Edit Distance Reward: Learning to Edit Scene Graph", European Conference on Computer Vision (ECCV), 2020
7. 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, Vol:29, pp.7834-7844, 2020
8. Hanrui Wu, Yuguang Yan, Yuzhong Ye, Michael K Ng, Qingyao Wu*, "Geometric Knowledge Embedding for Unsupervised Domain Adaptation", Knowledge-Based Systems, 191: 105155. 2020
9. Min Yang, Lei Chen, Ziyu Lyu, Junhao Liu, Ying Shen, Qingyao Wu, “Hierarchical fusion of common sense knowledge and classifier decisions for answer selection in community question answering”, 132, Neural Networks, 132, pp.53-65, 2020
[2019]
1. 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
2. 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
3. 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
4. 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: 3.015)
5. 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
6. 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
7. 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." In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), pp. 360-368. Springer, Cham, 2019
8. Shihao Zhang, Huazhu Fu, Yuguang Yan, Yubing Zhang, Qingyao Wu, Ming Yang, Mingkui Tan, Yanwu Xu, "Attention Guided Network for Retinal Image Segmentation", In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2019
9. 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", In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI),2019
10. 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
11. Pengshuai Yin, Qingyao Wu#, Yanwu Xu, Huaqing Min, Ming Yang, Yubing Zhang, Mingkui Tan, "PM-Net: Pyramid Multi-label Network for Joint Optic Disc and Cup Segmentation", 10th International Workshop on Machine Learning in Medical Imaging (MLMI), 2019
12. Yong Guo, Qi Chen, Jian Chen, Qingyao Wu, Qinfeng Shi, and Mingkui Tan, Auto-Embedding Generative Adversarial Networks For High Resolution Image Synthesis, 11(21), IEEE Transactions on Multimedia, 2019
13. 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”, 6th International Workshop on Ophthalmic Medical Image Analysis(OMIA), 2019
14. Zhang, Yifan, Chen, Hanbo, Wei, Ying, Zhao, Peilin, Cao, Jiezhang, Fan, Xinjuan, Lou, Xiaoying, Liu, Hailing, Hou, Jinlong, Han, Xiao, Yao, Jianhua, Wu, Qingyao, Tan, Mingkui, Huang, Junzhou, From Whole Slide Imaging to Microscopy: Deep Microscopy Adaptation Network for Histopathology Cancer Image Classification, 10th International Workshop on Machine Learning in Medical Imaging (MLMI), 2019
15. Min Yang, Qingnan Jiang, Ying Shen, Qingyao Wu, Zhou Zhao, Wei Zhou,,Hierarchical human-like strategy for aspect-level sentiment classification with sentiment linguistic knowledge and reinforcement learning, Neural Networks, 117, 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:8.793)
2. 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
3. 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
4. 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
5. 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
6. 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
7. 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
8. Yong Guo#, Qingyao Wu#, Jian Chen, Mingkui Tan, " Double forward propagation for memorized batch normalization", Association for the Advancement of Artificial Intelligence (AAAI), 2018
9. 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)
Siyu Jiang, Yonghui Xu, Hengjie Song, Qingyao Wu, Michael K. Ng, Huaqing Min, Shaojian Qiu, “Multi-instance transfer metric learning by weighted distribution and consistent maximum likelihood estimation”, Neurocomputing, 321, pp.49-60, 2018
https://www.scholat.com/wuqingyao
广州大学城华南理工大学软件学院B8
