Chen Gong (宫辰)'s Homepage


Publications (学术论文)


  • Note that the copyrights of the listed papers belong to the corresponding publishers, so you are not allowed to distribute them without permission. (本网页所列文章的版权归出版商所有,未经许可不得传播。)

  • The papers and codes on this page can only be used for research. They cannot be used for commercial purpose without permission. (本网页所列文章、代码仅供研究使用,未经许可不得用于商业用途。)

  • IEEE/ACM Transactions系列文章为相关领域的世界顶级期刊,AAAI、IJCAI为人工智能领域国际顶级会议,CVPR、ICCV、ECCV为计算机视觉领域国际顶级会议,ICML、NeurIPS、ICLR为机器学习领域国际顶级会议,KDD、ICDM为数据挖掘领域国际顶级会议。

[ 2024, 2023, 2022, 2021, 2020, 2019, 2018, 2017, 2016, 2015, 2014, 2013, 2012 ]


2024

  1. Mingyu Li, Tao Zhou, Bo Han, Tongliang Liu, Xinkai Liang, Jiajia Zhao, Chen Gong.
    Class-wise Contrastive Prototype Learning for Semi-Supervised Classification under Intersectional Class Mismatch.
    IEEE Transactions on Multimedia (TMM) , 2024.

  2. Hengmin Zhang, Jian Yang, Jianjun Qian, Chen Gong, Xin Ning, Zhiyuan Zha, Bihan Wen.
    Faster Nonconvex Low-rank Matrix Learning for Image Low-level and High-level Vision: A Unified Framework.
    Information Fusion (INF) , 2024.
    [ paper ]

  3. Cheng Zhang, Shengwei Zhong, Sheng Wan, Chen Gong.
    Easy-to-Hard Domain Adaptation with Human Interaction for Hyperspectral Image Classification.
    IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2024.

  4. Shuo Chen, Gang Niu, Chen Gong, Okan Koc, Jian Yang, Masashi Sugiyama.
    Robust Similarity Learning with Difference Alignment Regularization.
    International Conference on Learning Representations (ICLR), 2024.

  5. Xiaoqi An, Lin Zhao, Chen Gong, Nannan Wang, Di Wang, Jian Yang.
    SHaRPose: Sparse High-Resolution Representation for Human Pose Estimation.
    AAAI Conference on Artificial Intelligence (AAAI), 2024.


2023

  1. Xiaobo Xia, Pengqian Lu, Chen Gong, Bo Han, Jun Yu, Jun Yu, Tongliang Liu.
    Regularly Truncated M-Estimators for Learning With Noisy Labels.
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
    [ paper ] [ code ]

  2. Mingyu Li, Tao Zhou, Zhuo Huang, Jian Yang, Jie Yang, Chen Gong.
    Dynamic Weighted Adversarial Learning for Semi-Supervised Classification under Intersectional Class Mismatch.
    ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) , 2023.
    [ paper ] [ code ]

  3. Hengmin Zhang, Jiaoyan Zhang, Bob Zhang, Chen Gong, Jianjun Quan, Jian Yang.
    Unified Framework for Faster Clustering via Joint Schatten p-norm Factorization with Optimal Mean.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS) , 2023.
    [ paper ]

  4. Fei Zhang, Yunjie Ye, Lei Feng, Zhongwen Rao, Jieming Zhu, Marcus Kalander, Chen Gong, Jianye Hao, Bo Han.
    Exploiting Counter-Examples for Active Learning with Partial labels.
    Machine Learning (MLJ), 2023.
    [ paper ]

  5. Jialiang Tang, Shuo Chen, Gang Niu, Masashi Sugiyama, Chen Gong.
    Distribution Shift Matters for Knowledge Distillation with Webly Collected Images.
    The International Conference on Computer Vision (ICCV) , 2023.
    [ paper ] [ code ]

  6. Xiaobo Xia, Bo Han, Yibing Zhan, Jun Yu, Mingming Gong, Chen Gong, Tongliang Liu.
    Combating Noisy Labels with Sample Selection by Mining High-Discrepancy Examples.
    The International Conference on Computer Vision (ICCV) , 2023.
    [ paper ] [ code ]

  7. Shuo Chen, Chen Gong, Xiang Li, Jian Yang, Gang Niu, Masashi Sugiyama.
    Boundary-restricted Metric Learning.
    Machine Learning (MLJ), 2023.
    [ paper ]

  8. Tiansong Jiang, Sheng Wan, Chen Gong.
    Class-Imbalanced Semi-Supervised Learning with Inverse Auxiliary Classifier.
    The British Machine Vision Conference (BMVC) , 2023.
    [ paper ] [ code ]

  9. Yue Yuan, Sheng Wan, Chuang Zhang, Chen Gong.
    CASSOR: Class-Aware Sample Selection for Ordinal Regression with Noisy Labels.
    The Pacific Rim International Conference on Artificial Intelligence (PRICAI) , 2023.
    [ paper ] [ code ]

  10. Runtong Zhang, Hongyuan Zhu, Hanwang Zhang, Chen Gong, Joey Tianyi Zhou, Fanman Meng.
    Semi-Supervised Few-shot Segmentation with Noisy Support Images.
    IEEE International Conference on Image Processing (ICIP) , 2023.
    [ paper ]

  11. Sheng Wan, Yibing Zhan, Shuo Chen, Shirui Pan, Jian Yang, Dacheng Tao, Chen Gong.
    Boosting Graph Contrastive Learning via Adaptive Sampling.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS) , 2023.
    [ paper ]

  12. Weiming Mai, Jiangchao Yao, Chen Gong, Ya Zhang, Yiu-Ming Cheung, Bo Han.
    Server-Client Collaborative Distillation for Federated Reinforcement Learning.
    ACM Transactions on Knowledge Discovery from Data (TKDD), 2023.
    [ paper ]

  13. Sheng Wan, Jian Yang, Chen Gong.
    Advances of Hyperspectral Image Classification Based on Graph Neural Networks.
    Acta Electronica Sinica (《电子学报》in Chinese), 2023.
    [ paper ]

  14. Zicheng Zhao (equal contribution), Linhao Luo (equal contribution), Shirui Pan, Quoc Viet Hung Nguyen, Chen Gong.
    Towards Few-shot Inductive Link Prediction on Knowledge Graphs: A Relational Anonymous Walk-guided Neural Process Approach.
    The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2023.
    [ paper ]

  15. Tao Zhou, Yi Zhou, Kelei He, Chen Gong, Jian Yang, Huazhu Fu, Dinggang Shen.
    Cross-level Feature Aggregation Network for Polyp Segmentation.
    Pattern Recognition (PR), 2023.
    [ paper ]

  16. Zhuo Huang, Miaoxi Zhu, Xiaobo Xia, Li Shen, Jun Yu, Chen Gong, Bo Han, Bo Du, Tongliang Liu.
    Robust Generalization against Corruptions via Worst-Case Sharpness Minimization.
    IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
    [ paper ] [ code ]

  17. Chenhong Zhou, Feng Liu, Chen Gong, Rongfei Zeng, Tongliang Liu, William Cheung, Bo Han Zhuo Huang, Xiaobo Xia, Li Shen, Bo Han.
    KRADA: Known-region-aware Domain Alignment for Open-set Domain Adaptation in Semantic Segmentation.
    Transactions on Machine Learning Research (TMLR), 2023.
    [ paper ]

  18. Zhuo Huang, Xiaobo Xia, Li Shen, Bo Han, Mingming Gong, Chen Gong, Tongliang Liu.
    Harnessing Out-Of-Distribution Examples via Augmenting Content and Style.
    International Conference on Learning Representations (ICLR), 2023.
    [ paper ] [ code ]

  19. Wentao Yu, Sheng Wan, Jian Yang, Chen Gong.
    Hyperspectral Image Classification With Contrastive Graph Convolutional Network.
    IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2023.
    [ESI highly cited paper, paper ]


2022

  1. Zhenyuan Chen, Zhendong Wang, Chen Gong.
    Image-level Labeled Weakly Supervised Object Detection: A Survey.
    Journal of Image and Graphics (JOS, 《中国图象图形学报》in Chinese), 2022.
    [ paper ]

  2. Chen Gong, Muhammad Imran Zulfiqar, Chuang Zhang, Shahid Mahmood, Jian Yang.
    A Recent Survey on Instance-Dependent Positive and Unlabeled Learning.
    Fundamental Research (FMRE), 2022.
    [ paper ]

  3. Tao Zhou, Yi Zhou, Chen Gong, Jian Yang, Yu Zhang.
    Feature Aggregation and Propagation Network for Camouflaged Object Detection.
    IEEE Transactions on Image Processing (TIP), 2022.

  4. Shuo Chen, Chen Gong, Jun Li, Jian Yang, Gang Niu, Masashi Sugiyama.
    Learning Contrastive Embedding in Low-Dimensional Space.
    Annual Conference on Neural Information Processing Systems (NeurIPS), 2022.
    [ paper ]

  5. Qizhou Wang, Feng Liu, Yonggang Zhang, Jing Zhang, Chen Gong, Tongliang Liu, Bo Han.
    Watermarking for Out-of-distribution Detection.
    Annual Conference on Neural Information Processing Systems (NeurIPS), 2022.
    [ paper ] [ code ]

  6. Yizhen Zheng, Yu Zheng, Xiaofei Zhou, Chen Gong, Vincent CS Lee, and Shirui Pan.
    Unifying Graph Contrastive Learning with Flexible Contextual Scopes.
    IEEE International Conference on Data Mining (ICDM), 2022.
    [ paper ]

  7. Xianye Ben, Chen Gong, Tianhuan Huang, Chuanye Li, Rui Yan, Yujun Li.
    Tackling Micro-Expression Data Shortage via Dataset Alignment and Active Learning.
    IEEE Transactions on Multimedia (TMM) , 2022.
    [ paper ]

  8. Zhendong Wang, Zhenyuan Chen, Chen Gong.
    Class Activation Map Refinement via Semantic Affinity Exploration for Weakly Supervised Object Detection.
    IEEE International Conference on Image Processing (ICIP) , 2022.
    [ paper ]

  9. Hengmin Zhang, Feng Qian, Peng Shi, Wenli Du, Yang Tang, Jianjun Qian, Chen Gong, Jian Yang.
    Generalized Nonconvex Nonsmooth Low-rank Matrix Recovery Framework with Feasible Algorithm Designs and Convergence Analysis.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS) , 2022.
    [ paper ]

  10. Chuang Zhang, Li Shen, Jian Yang, Chen Gong.
    Towards Harnessing Feature Embedding for Robust Learning with Noisy Labels.
    Machine Learning (MLJ), 2022.
    [ paper ]

  11. Chen Gong, Yongliang Ding, Bo Han, Gang Niu, Jian Yang, Jane You, Dacheng Tao, Masashi Sugiyama.
    Class-Wise Denoising for Robust Learning under Label Noise.
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
    [ paper ] [ code ]

  12. Zhuo Huang, Jian Yang, Chen Gong.
    They are Not Completely Useless: Towards Recycling Transferable Unlabeled Data for Class-Mismatched Semi-Supervised Learning.
    IEEE Transactions on Multimedia (TMM), 2022.
    [ paper ] [ code ]

  13. Chaojian Yu, Bo Han, Li Shen, Jun Yu, Chen Gong, Mingming Gong, Tongliang Liu.
    Understanding Robust Overfitting of Adversarial Training and Beyond.
    International Conference on Machine Learning (ICML), 2022.
    [ paper ]

  14. Tianhuan Huang, Xianye Ben, Chen Gong, Baochang Zhang, Rui Yan, Qiang Wu.
    Enhanced Spatial-Temporal Salience for Cross-view Gait Recognition.
    IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2022.
    [ paper ]

  15. Sheng Wan, Shirui Pan, Shengwei Zhong, Jie Yang, Jian Yang, Yibing Zhan, Chen Gong.
    Multi-Level Graph Learning Network for Hyperspectral Image Classification.
    Pattern Recognition (PR), 2022.
    [ paper ] [ code ]

  16. Cheng Zhang, Shenwei Zhong, Chen Gong.
    Feature Integration-based Training For Cross-domain Hyperspectral Image Classification.
    The International Geoscience and Remote Sensing Symposium (IGARSS), 2022.

  17. Xun Feng, Jian Yang, Tao Zhou, Chen Gong.
    Attention Mechanism and Categorical Hierarchy Based Weakly Supervised Object Localization.
    Journal of Software (JOS, 《软件学报》in Chinese), 2022.
    [ paper ]

  18. Tao Zhou, Huazhu Fu, Chen Gong, Ling Shao, Fatih Porikli, Haibin Ling, Jianbing Shen.
    Consistency and Diversity induced Human Motion Segmentation.
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
    [ESI highly cited paper, paper ]

  19. Yongliang Ding, Tao Zhou, Chuang Zhang, Yijing Luo, Juan Tang, Chen Gong.
    Multi-class Label Noise Learning via Loss Decomposition and Centroid Estimation.
    SIAM International Conference on Data Mining (SDM), 2022.
    [ paper ]


2021

  1. Shengwei Zhong, Tao Zhou, Sheng Wan, Jian Yang, Chen Gong.
    Dynamic Spectral-Spatial Poisson Learning for Hyperspectral Image Classification with Extremely Scarce Labels.
    IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2021.
    [ paper ]

  2. Yu Yao, Baosheng Yu, Chen Gong, Tongliang Liu.
    Understanding How Pre-Training Regularizes Deep Learning Algorithms.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021.
    [ paper ]

  3. Zhuo Huang, Chao Xue, Bo Han, Jian Yang, Chen Gong.
    Universal Semi-Supervised Learning.
    Annual Conference on Neural Information Processing Systems (NeurIPS), 2021.
    [ paper ] [ code ]

  4. Sheng Wan, Yibing Zhan, Liu Liu, Baosheng Yu, Shirui Pan, Chen Gong.
    Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels.
    Annual Conference on Neural Information Processing Systems (NeurIPS), 2021.
    [ paper ] [ code ]

  5. Qizhou Wang, Feng Liu, Bo Han, Tongliang Liu, Chen Gong, Gang Niu, Mingyuan Zhou, Masashi Sugiyama.
    Probabilistic Margins for Instance Reweighting in Adversarial Training.
    Annual Conference on Neural Information Processing Systems (NeurIPS), 2021.
    [ paper ] [ code ]

  6. Minnan Luo, Xiaojun Chang, Chen Gong.
    Reliable Shot Identification for Complex Event Detection via Visual-Semantic Embedding.
    Computer Vision and Image Understanding (CVIU), 2021.
    [ paper ]

  7. Chuang Zhang (equal contribution), Qizhou Wang (equal contribution), Tengfei Liu, Xun Lu, Jin Hong, Bo, Han, Chen Gong.
    Fraud Detection under Multi-Sourced Extremely Noisy Annotations.
    The Conference on Information and Knowledge Management (CIKM), 2021.
    [ paper ]

  8. Lin Zhao, Nannan Wang, Chen Gong, Jian Yang, Xinbo Gao.
    Estimating Human Pose Efficiently by Parallel Pyramid Networks.
    IEEE Transactions on Image Processing (TIP), 2021.
    [ paper ]

  9. Xiaofei Zhou, Kunye Shen, Chen Gong, Zhi Liu, Jiyong Zhang, Chenggang Yan.
    Edge-aware Multi-scale Feature Integration Network for Salient Object Detection in Optical Remote Sensing Images.
    IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2021.
    [ paper ]

  10. Dayong Tian, Chen Gong, Maoguo Gong, Yiwen Wei, Xiaoxuan Feng.
    Modeling Cardinality in Image Hashing.
    IEEE Transactions on Cybernetics (TCYB), 2021.
    [ paper ]

  11. Tongtong Che, Yuanjie Zheng, Yunshuai Yang, Sujuan Hou, Weikuan Jia, Jie Yang, Chen Gong.
    SDOF-GAN: Symmetric Dense Optical Flow Estimation with Generative Adversarial Networks.
    IEEE Transactions on Image Processing (TIP), 2021.
    [ paper ]

  12. Shuo Chen, Gang Niu, Chen Gong, Jun Li, Jian Yang, Masashi Sugiyama.
    Large-margin Contrastive Learning with Distance Polarization Regularizer.
    International Conference on Machine Learning (ICML), 2021.
    [ paper ]

  13. Ming Jin, Yizhen Zheng, Yuan-Fang Li, Chen Gong, Chuan Zhou, Shirui Pan.
    Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning.
    International Joint Conference on Artificial Intelligence (IJCAI), 2021.
    [ paper ]

  14. Sheng Wan, Shirui Pan, Ping Zhong, Xiaojun Chang, Jian Yang, Chen Gong.
    Dual Interactive Graph Convolutional Networks for Hyperspectral Image Classification.
    IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2021.
    [ paper ]

  15. Yixin Liu, Zhao Li, Shirui Pan, Chen Gong, Chuan Zhou, George Karypis.
    Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021.
    [ paper ]

  16. Chen Gong, Qizhou Wang, Tongliang Liu, Bo Han, Jane You, Jian Yang, Masashi Sugiyama.
    Instance-Dependent Positive and Unlabeled Learning with Labeling Bias Estimation.
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
    [ paper ]

  17. Xiaobo Xia, Tongliang Liu, Bo Han, Chen Gong, Nannan Wang, Zongyuan Ge, Yi Chang.
    Robust early-learning: Hindering the memorization of noisy labels.
    International Conference on Learning Representations (ICLR), 2021.
    [ paper ] [ code ]

  18. Xiuhua Chen, Chen Gong, Jian Yang.
    Cost-Sensitive Positive and Unlabeled Learning.
    Information Sciences (INS), 2021.
    [ paper ]

  19. Sheng Wan, Shirui Pan, Jian Yang, Chen Gong.
    Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning.
    AAAI Conference on Artificial Intelligence (AAAI), 2021.
    [ paper ] [ code ]

  20. Qizhou Wang, Bo Han, Tongliang Liu, Gang Niu, Jian Yang, Chen Gong.
    Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model.
    AAAI Conference on Artificial Intelligence (AAAI), 2021.
    [ paper ] [ code ]

  21. Qizhou Wang, Jiangchao Yao, Chen Gong, Tongliang Liu, Mingming Gong, Hongxia Yang, Bo Han.
    Learning with Group Noise.
    AAAI Conference on Artificial Intelligence (AAAI), 2021.
    [ paper ] [ code ]


2020

  1. Chen Gong, Jian Yang, Jane You, Masashi Sugiyama.
    Centroid Estimation with Guaranteed Efficiency: A General Framework for Weakly Supervised Learning.
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.
    [ ESI highly cited paper, paper ] [ code ]

  2. Jiehui Deng, Sheng Wan, Xiang Wang, Enmei Tu, Xiaolin Huang, Jie Yang, Chen Gong.
    Edge-Aware Graph Attention Network for Ratio of Edge-User Estimation in Mobile Networks.
    International Conference on Pattern Recognition (ICPR), 2020.
    [ paper ]

  3. Fanghui Liu, Xiaolin Huang, Chen Gong, Jie Yang, Li Li.
    Learning Data-adaptive Non-parametric Kernels.
    Journal of Machine Learning Research (JMLR), 2020.
    [ paper ]

  4. Lin Zhao, Jie Xu, Chen Gong, Jian Yang, Wangmeng Zuo, Xinbo Gao.
    Learning to Acquire the Quality of Human Pose Estimation.
    IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2020.
    [ paper ]

  5. Xuxi Chen, Wuyang Chen, Tianlong Chen, Ye Yuan, Chen Gong, Kewei Chen, Zhangyang Wang.
    Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training.
    International Conference on Machine Learning (ICML), pp. 1944-1954, 2020.
    [ paper ]

  6. Yao Yao, Chen Gong, Jiehui Deng, Jian Yang.
    Network Cooperation with Progressive Disambiguation for Partial Label Learning.
    The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2020.
    [ paper ]

  7. Yijing Luo, Bo Han, Chen Gong.
    A Bi-level Formulation for Label Noise Learning with Spectral Cluster Discovery.
    International Joint Conference on Artificial Intelligence (IJCAI), pp. 2605-2611, 2020.
    [ paper ]

  8. Chuang Zhang, Chen Gong, Tengfei Liu, Xun Lu, Weiqiang Wang, Jian Yang.
    Online Positive and Unlabeled Learning.
    International Joint Conference on Artificial Intelligence (IJCAI), pp. 2248-2254, 2020.
    [ paper ]

  9. Guojia Wan, Shirui Pan, Chen Gong, Chuan Zhou, Gholamreza Haffari.
    Reasoning Like Human: Hierarchical Reinforcement Learning for Knowledge Graph Reasoning.
    International Joint Conference on Artificial Intelligence (IJCAI), pp. 1926-1932, 2020.
    [ paper ]

  10. Tao Zhou, Huazhu Fu, Chen Gong, Jianbing Shen, Ling Shao, Fatih Porikli.
    Multi-mutual Consistency Induced Transfer Subspace Learning for Human Motion Segmentation.
    IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), pp. 10277-10286, 2020.
    [ paper ]

  11. Yao Yao, Jiehui Deng, Xiuhua Chen, Chen Gong, Jianxin Wu, Jian Yang.
    Deep Discriminative CNN with Temporal Ensembling for Ambiguously-Labeled Image Classification.
    AAAI Conference on Artificial Intelligence (AAAI), pp. 12669-12676, 2020.
    [ paper ]

  12. Sheng Wan, Ping Zhong, Shirui Pan, Jian Yang, Guangyu Li, Chen Gong.
    Hyperspectral Image Classification With Context-Aware Dynamic Graph Convolutional Network.
    IEEE Transactions on Geoscience and Remote Sensing (TGRS), pp. 1-16, 2020.
    [ ESI highly cited paper, paper ]

  13. Lin Zhao, Jie Xu, Shanshan Zhang, Chen Gong, Jian Yang, Xinbo Gao.
    Perceiving Heavily Occluded Human Poses by Assigning Unbiased Score.
    Information Sciences (INS), 2020.
    [ paper ]

  14. Lei Zhou, Chen Gong, Zhi Liu, Keren Fu.
    SAL: Selection and Attention Losses for Weakly Supervised Semantic Segmentation.
    IEEE Transactions on Multimedia (TMM), 2020.
    [ paper ]


2019

  1. Xiaobo Xia, Tongliang Liu, Nannan Wang, Bo Han, Chen Gong, Gang Niu, Masashi Sugiyama.
    Are Anchor Points Really Indispensable in Label-Noise Learning?
    Annual Conference on Neural Information Processing Systems (NeurIPS), pp. 6838-6849, 2019.
    [ paper ] [ code ]

  2. Shuo Chen, Lei Luo, Jian Yang, Chen Gong, Jun Li, Heng Huang.
    Curvilinear Distance Metric Learning.
    Annual Conference on Neural Information Processing Systems (NeurIPS), pp. 4223-4232, 2019.
    [ paper ]

  3. Chuang Zhang, Dexin Ren, Tongliang Liu, Jian Yang, Chen Gong.
    Positive and Unlabeled Learning with Label Disambiguation.
    International Joint Conference on Artificial Intelligence (IJCAI), pp.4250-4256, 2019.
    [ paper ]

  4. Le Hui, Xiang Li, Chen Gong, Meng Fang, Joey Tianyi Zhou, Jian Yang.
    Inter-Class Angular Loss for Convolutional Neural Networks.
    AAAI Conference on Artificial Intelligence (AAAI), pp. 3894-3901, 2019.
    [ paper ]

  5. Shuo Chen, Chen Gong, Jian Yang, Ying Tai, Lei Hui, Jun Li.
    Data-Adaptive Metric Learning with Scale Alignment.
    AAAI Conference on Artificial Intelligence (AAAI), pp. 3347-3354, 2019.
    [ paper ]

  6. Chen Gong, Hong Shi, Tongliang Liu, Chuang Zhang, Jian Yang, Dacheng Tao.
    Loss Decomposition and Centroid Estimation for Positive and Unlabeled Learning.
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019.
    [ paper ]

  7. Chen Gong, Jian Yang, Dacheng Tao.
    Multi-modal Curriculum Learning over Graphs.
    ACM Transactions on Intelligent Systems and Technology (TIST), vol. 10, no. 04, pp. 25, 2019.
    [ paper ]

  8. Chen Gong, Hong Shi, Jie Yang, Jian Yang.
    Multi-Manifold Positive and Unlabeled Learning for Visual Analysis.
    IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 30, no. 05, pp. 1396-1409, 2019.
    [ paper ]

  9. Chen Gong, Tongliang Liu, Jian Yang, Dacheng Tao.
    Large-Margin Label-Calibrated Support Vector Machines for Positive and Unlabeled Learning.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 30, no. 11, pp. 3471-3483, 2019.
    [ paper ] [ code ]

  10. Hengmin Zhang, Jianjun Qian, Bob Zhang, Jian Yang, Chen Gong, Yang Wei.
    Low-Rank Matrix Recovery via Modified Schatten-p Norm Minimization with Convergence Guarantees.
    IEEE Transactions on Image Processing (TIP), vol. 29, pp. 3132-3142, 2019.
    [ paper ]

  11. Xianye Ben, Chen Gong, Peng Zhang, Xitong Jia, Qiang Wu, Weixiao Meng.
    Coupled Patch Alignment for Matching Cross-view Gaits.
    IEEE Transactions on Image Processing (TIP), vol. 28, no. 06, pp. 3142-3157, 2019.
    [ paper ]

  12. Jingchen Ke, Chen Gong, Tongliang Liu, Lin Zhao, Jian Yang, Dacheng Tao.
    Laplacian Welsch Regularization for Robust Semi-Supervised Learning.
    IEEE Transactions on Cybernetics (TCYB), 2019.
    [ paper ]

  13. Tao Zhou, Changqing Zhang, Chen Gong, Harish Bhaskar, Jie Yang.
    Multiview Latent Space Learning with Feature Redundancy Minimization.
    IEEE Transactions on Cybernetics (TCYB), vol. 50, no. 4, pp. 1655-1668, 2019.
    [ paper ]

  14. Shuo Chen, Jian Yang, Yang Wei, Lei Luo, Gui-fu Lu, Chen Gong.
    Delta-Norm-Based Robust Regression with Applications to Image Analysis.
    IEEE Transactions on Cybernetics (TCYB), pp. 1-13, 2019.
    [ paper ]

  15. Sheng Wan, Chen Gong, Ping Zhong, Bo Du, Lefei Zhang, Jian Yang.
    Multiscale Dynamic Graph Convolutional Network for Hyperspectral Image Classification.
    IEEE Transactions on Geoscience and Remote Sensing (TGRS), vol. 59, no. 5, pp. 3162-3177, 2019.
    [ ESI highly cited paper, paper ] [ code ]

  16. Donna Xu, Yaxin Shi, Ivor Tsang, Yew-Soon Ong, Chen Gong, Xiaobo Shen.
    A Survey on Multi-output Learning.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 31, no. 7, pp. 2409-2429, 2019.
    [ paper ]

  17. Yang Wei, Chen Gong, Shuo Chen, Tongliang Liu, Jian Yang, Dacheng Tao.
    Harnessing Side Information for Classification under Label Noise.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2019.
    [ paper ]

  18. Hengmin Zhang, Chen Gong, Jianjun Qian, Bob Zhang, Chunyan Xu, Jian Yang.
    Efficient Recovery of Low Rank Matrix via Double Nonconvex Nonsmooth Rank Minimization.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 30, no. 10, pp. 2916-2925, 2019.
    [ paper ]

  19. Chao Ma, Chen Gong, Xiang Li, Xiaolin Huang, Jie Yang.
    Towards Making Unsupervised Graph Hashing Discriminative.
    IEEE Transactions on Multimedia (TMM), vol. 22, no. 3, pp. 760-774, 2019.
    [ paper ]

  20. Xianye Ben, Chen Gong, Peng Zhang, Rui Yan, Qiang Wu, Weixiao Meng.
    Coupled Bilinear Discriminant Projection for Cross-view Gait Recognition.
    IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 30, no. 3, pp. 734-747, 2019.
    [ ESI highly cited paper, paper ]


2018

  1. Chen Gong, Xiaojun Chang, Meng Fang, Jian Yang.
    Teaching Semi-Supervised Classifier via Generalized Distillation.
    International Joint Conference on Artificial Intelligence (IJCAI), pp. 2156-2162, 2018.
    [ paper ] [ a href="code/GDSSL_IJCAI18.rar">code ]

  2. Shuo Chen, Chen Gong, Jian Yang.
    Adversarial Metric Learning.
    International Joint Conference on Artificial Intelligence (IJCAI), pp. 2021-2027, 2018.
    [ paper ] [ code ]

  3. Hong Shi, Shaojun Pan, Jian Yang, Chen Gong.
    Positive and Unlabeled Learning via Loss Decomposition and Centroid Estimation.
    International Joint Conference on Artificial Intelligence (IJCAI), pp. 2689-2695, 2018.
    [ paper ]

  4. Fanghui Liu, Xiaolin Huang, Chen Gong, Jie Yang.
    Nonlinear Pairwise Layer and Its Training for Kernel Learning.
    AAAI Conference on Artificial Intelligence (AAAI), pp. 3659-3666, 2018.
    [ paper ]

  5. Fanghui Liu, Chen Gong, Xiaolin Huang, Tao Zhou, Jie Yang, Dacheng Tao.
    Robust Visual Tracking Revisited: From Correlation Filter to Template Matching.
    IEEE Transactions on Image Processing (TIP), vol. 27, no. 6, pp. 2777-2790, 2018.
    [ paper ]

  6. Hengmin Zhang, Jian Yang, Fanhua Shang, Chen Gong, Zhenyu Zhang.
    LRR for Subspace Segmentation via Tractable Schatten-p Norm Minimization and Factorization.
    IEEE Transactions on Cybernetics (TCYB), vol. 49, no. 5, pp. 1722-1734, 2018.
    [ paper ] [ code ]

  7. Joey Tianyi Zhou, Meng Fang, Hao Zhang, Chen Gong, Xi Peng, Zhiguo Cao, Rick Siow Mong Goh.
    Learning with Annotation of Various Degrees.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 30, no. 9, pp. 2794-2804, 2018.
    [ paper ]

  8. Fanghui Liu, Xiaolin Huang, Chen Gong, Jie Yang, Johan A. K. Suykens.
    Indefinite Kernel Logistic Regression with Concave-inexact-convex Procedure.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 30, no. 3, pp. 765-776, 2018.
    [ paper ]

  9. Xiaofei Zhou, Zhi Liu, Chen Gong, Wei Liu.
    Improving Video Saliency Detection via Localized Estimation and Spatiotemporal Refinement.
    IEEE Transactions on Multimedia (TMM), vol. 20, no. 11, pp. 2993-3007, 2018.
    [ paper ]

  10. Bi-Ke Chen, Chen Gong, Jian Yang.
    Importance-Aware Semantic Segmentation for Autonomous Vehicles.
    IEEE Transactions on Intelligent Transportation System (TITS), vol. 20, no. 1, pp. 137-148, 2018.
    [ paper ]


2017

  1. Chen Gong, Hengmin Zhang, Jian Yang, Dacheng Tao.
    Learning with Inadequate and Incorrect Supervision.
    IEEE International Conference on Data Mining (ICDM), pp. 889-894, 2017.
    [ paper ] [ code ]

  2. Chen Gong.
    Exploring Commonality and Individuality for Multi-modal Curriculum Learning.
    AAAI Conference on Artificial Intelligence (AAAI), pp. 1926-1933, 2017.
    [ paper ] [ code ]

  3. Bi-Ke Chen, Chen Gong, Jian Yang.
    Importance-Aware Semantic Segmentation for Autonomous Driving System.
    International Joint Conference on Artificial Intelligence (IJCAI), pp. 1504-1510, 2017.
    [ paper ]

  4. Chen Gong, Dacheng Tao, Xiaojun Chang, Jian Yang.
    Ensemble Teaching for Hybrid Label Propagation.
    IEEE Transactions on Cybernetics (TCYB), vol. 49, no. 2, pp. 388-402, 2017.
    [ paper ]

  5. Chen Gong, Tongliang Liu, Yuanyan Tang, Jian Yang, Jie Yang, Dacheng Tao.
    A Regularization Approach for Instance-based Superset Label Learning.
    IEEE Transactions on Cybernetics (TCYB), vol. 48, no. 3, pp. 967-978, 2017.
    [ paper ] [ code ]

  6. Chen Gong, Dacheng Tao, Wei Liu, Liu Liu, Jie Yang.
    Label Propagation via Teaching-to-Learn and Learning-to-Teach.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 28, no. 6, pp. 1452-1465, 2017.
    [ paper ] [ code ]

  7. Junxia Li, Jian Yang, Chen Gong, Qingshan Liu.
    Saliency fusion via sparse and double low rank decomposition.
    Pattern Recognition Letters (PRL), vol. 107, pp. 114-122, 2017.
    [ paper ]

  8. Chao Ma, Chen Gong, Yun Gu, Jie Yang, Deying Feng.
    SHISS: Supervised hashing with informative set selection.
    Pattern Recognition Letters (PRL), vol. 107, pp. 105-113, 2017.
    [ paper ]

  9. Tao Zhang, Wenjing Jia, Chen Gong, Jun Sun, Xiaoning Song.
    Semi-supervised Dictionary Learning via Local Sparse Constraints for Violence Detection.
    Pattern Recognition Letters (PRL), vol. 107, pp. 98-104, 2017.
    [ paper ]

  10. Fanghui Liu, Chen Gong, Tao Zhou, Keren Fu, Jie Yang.
    Inverse Nonnegative Local Coordinate Factorization for Visual Tracking.
    IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 28, no. 8, pp. 1752-1764, 2017.
    [ paper ]

  11. Fanghui Liu, Tao Zhou, Chen Gong, Keren Fu, Li Bai, and Jie Yang.
    Visual Tracking via Nonnegative Multiple Coding.
    IEEE Transactions on Multimedia (TMM), vol. 19, no. 12, pp. 2680-2691, 2017.
    [ paper ]


2016

  1. Chen Gong, Dacheng Tao, Jie Yang.
    Teaching-to-Learn and Learning-to-Teach For Multi-label Propagation.
    AAAI Conference on Artificial Intelligence (AAAI), pp. 1610-1616, 2016.
    [ paper ] [ code ]

  2. Long Lan, Dacheng Tao, Chen Gong, Naiyang Guan, Zhigang Luo.
    Online Multi-object Tracking by Quadratic Pseudo-Boolean Optimization.
    International Joint Conference on Artificial Intelligence (IJCAI), pp. 3396-3402, 2016.
    [ paper ]

  3. Chen Gong, Dacheng Tao, Stephen Maybank, Wei Liu, Guoliang Kang, Jie Yang.
    Multi-modal Curriculum Learning for Semi-supervised Image Classification.
    IEEE Transactions on Image Processing (TIP), vol. 25, no. 7, pp. 3249-3260, 2016.
    [ ESI highly cited paper, paper ] [ code ]


2015

  1. Chen Gong, Dacheng Tao, Wei Liu, S.J. Maybank, Meng Fang, Keren Fu, Jie Yang.
    Saliency Propagation From Simple To Difficult.
    IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2531-2539, 2015.
    [ paper ] [ code ]

  2. Keren Fu, Chen Gong, Irene Gu, Jie Yang, Pengfei Shi.
    Salient object detection using normalized cut and geodesics.
    IEEE International Conference on Image Processing (ICIP), pp. 1100-1104, 2015.
    [ paper ]

  3. Chen Gong, Tongliang Liu, Dacheng Tao, Keren Fu, Jie Yang.
    Deformed graph Laplacian for semi-supervised learning.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 26, no. 10, pp. 2261-2274, 2015.
    [ paper ] [ code ]

  4. Chen Gong, Dacheng Tao, Keren Fu, Jie Yang.
    Fick’s Law Assisted Propagation for semi-supervised learning.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 26, no. 9, pp. 2148-2162, 2015.
    [ paper ] [ code ]

  5. Keren Fu, Chen Gong, Irene Gu, Jie Yang.
    Normalzied Cut-based Saliency Detection by Adaptive Multi-Level Region Merging.
    IEEE Transactions on Image Processing (TIP), vol. 24, no. 12, pp. 5671-5683, 2015.
    [ paper ]


2014

  1. Chen Gong, Dacheng Tao, Keren Fu, Jie Yang.
    ReLISH: Reliable Label Inference via Smoothness Hypothesis.
    AAAI Conference on Artificial Intelligence (AAAI), pp. 1840-1846, 2014.
    [ paper ]

  2. Chen Gong, Dacheng Tao, Keren Fu, Jie Yang.
    Signed Laplacian embedding for supervised dimension reduction.
    AAAI Conference on Artificial Intelligence (AAAI), pp. 1847-1853, 2014.
    [ paper ] [ code ]

  3. Zhongjie Yu, Chen Gong, Jie Yang, Li Bai.
    Pedestrian counting based on spatial and temporal analysis.
    IEEE International Conference on Image Processing (ICIP), pp. 2432-2436, 2014.
    [ paper ]

  4. Keren Fu, Chen Gong, Irene Y.H. Gu, Jie Yang, Xiangjian He.
    Spectral salient object detection.
    IEEE International Conference on Multimedia and Expo (ICME), pp. 1-6, 2014.
    [ paper ]

  5. Keren Fu, Chen Gong, Yixiao Yun, Yijun Li, Irene Gu, Jie Yang, Jingyi Yu.
    Adaptive Multi-Level Region Merging for Salient Object Detection.
    British Machine Vision Conference (BMVC), 2014.
    [ paper ]

  6. Keren Fu, Irene Gu, Yixiao Yun, Chen Gong, Jie Yang.
    Graph construction for salient object detection in videos.
    International Conference on Pattern Recognition (ICPR), 2014.
    [ paper ]

  7. Long Xu, Chen Gong, Qiang Wu, Jie Yang.
    Violent video detection based on MoSIFT feature and sparse coding.
    IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 3538-3542, 2014.
    [ paper ]

  8. Keren Fu, Kai Xie, Chen Gong, Irene Gu, Jie Yang.
    Violent video detection based on MoSIFT feature and sparse coding.
    IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 8110-8114, 2014.
    [ paper ]

  9. Chen Gong, Keren Fu, Qiang Wu, Enmei Tu, Jie Yang.
    Semi-supervised classification with pairwise constraints.
    Neurocomputing , vol. 139, pp. 130-137, 2014.
    [ paper ]


2013

  1. Keren Fu, Chen Gong, Irene Gu, Jie Yang.
    Geodesic saliency propagation for image salient region detection.
    IEEE International Conference on Image Processing (ICIP), pp. 3278-3282, 2013.
    [ paper ]

  2. Lei Zhou, Chen Gong, Yijun Li, Yu Qiao, Jie Yang.
    Salient object segmentation based on automatical labeling.
    International Conference on Neural Information Processing (ICONIP), pp 584-591, 2013.
    [ paper ]

  3. Chen Gong, Keren Fu, Artur Loza, Qiang Wu, Jia Liu, Jie Yang.
    PageRank Tracker: From Ranking to Tracking.
    IEEE Transactions on Cybernetics (TCYB), vol. 44, no. 6, pp. 882-893, 2013.
    [ paper ]


2012

  1. Chen Gong, Yang Liu, Tianyu Li, Jie Yang, Xiangjian He.
    The extended co-learning framework for robust object tracking.
    IEEE International Conference on Multimedia and Expo (ICME), pp. 398-403, 2012.
    [ paper ]

  2. Keren Fu, Chen Gong, Jie Yang, Yue Zhou.
    Salient object detection via color contrast and color distribution.
    Asian Conference on Computer Vision (ACCV), pp. 111-122, 2012.
    [ paper ]