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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、ICDE、ICDM为数据挖掘领域国际顶级会议。
(* indicates equal contributions and # indicates advisees)
Ruidong Fan, Xiao Ouyang, Tingjin Luo, Chenping Hou. Label Shift Correction via Confidence-Guided Self-Training. NeurIPS, 2023, Review. (CCF A) [PDF]
Feijiang Li, Yuhua Qian, Jieting Wang, Hongren Yan, Tingjin Luo. How Relation Enrichment Improves Clustering Ensemble Performance: A Second Order Induced Relation View, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025, Under Review.
(* indicates equal contributions, and # indicates advisees)
Hao Zhou, Tingjin Luo#, Jun Zhang, Guoli Li,Exploring the Essence of Relationships for Scene Graph Generation via Causal Features Enhancement Network, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025, Accepted. (JCR Q1, CCF A, IF: 20.8) [PDF]
Quangjiang Li, Tingjin Luo#, Jiahui Liao. Deep Multi-View Multi-Label Learning with Incomplete Views and Noisy Labels. Proceedings of IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2025, Accepted. (CCF A类会议)
Zhangqi Jiang, Junkai Chen, Beier Zhu, Tingjin Luo#, Yankun Shen, Xu Yang#. Devils in Middle Layers of Large Vision-Language Models: Interpreting, Detecting and Mitigating Object Hallucinations via Attention Lens. Proceedings of IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2025, Accepted. (CCF A类会议)
Hao Zhou, Tingjin Luo#, Yongming He, Jun Zhang. Dynamic Multi-experts Collaboration Learning for Long-tailed Visual Recognition, Information Fusion, Volume 115, 102734, March 2025. https://doi.org/10.1016/j.inffus.2024.102734. (CAAI A, JCR Q1, IF: 14.7)
Yueying Liu, Tingjin Luo#. Nonconvex and discriminative transfer subspace learning for unsupervised domain adaptation. Frontiers of Computer Science, 2025, 19(2): 192307. (JCR Q2, CCF B) [PDF]
Xinyue Zhang, Tingjin Luo#. Imbalanced Multi-instance Multi-label Learning via Tensor Product-based Semantic Fusion. Frontiers of Computer Science, 2024, Accepted. (JCR Q2, CCF B)
Quanjiang Li, Tingjin Luo#, Mingdie Jiang, Zhangqi Jiang, Chenping Hou, Feijiang Li. Semi-Supervised Multi-View Multi-Label Learning with View-Specific Transformer and Enhanced Pseudo-Label. Proceedings of the Thirty-Nineth AAAI Conference on Artificial Intelligence, 2025, Accepted. (CCF A类会议)
Hao Zhou, Tingjin Luo#, Zhangqi Jiang. Core-to-Global Reasoning for Compositional Visual Question Answering. Proceedings of the Thirty-Nineth AAAI Conference on Artificial Intelligence, 2025, Accepted. (CCF A类会议)
Tingjin Luo, Yang Yang#, Dongyun Yi, Jieping Ye. Robust discriminative feature learning with calibrated data reconstruction and sparse low-rank model, Applied Intelligence, vol. 54, 2867–2880 (2024). (ESI, JCR Q2, IF: 3.4)[PDF]
Wenzhang Zhuge, Tingjin Luo#, Hong Tao, Chenping Hou#, Dongyun Yi, Absent Multi-view Semi-supervised Classification, IEEE Transactions on Cybernetics, 54(3): 1708 - 1721, March 2024. (JCR Q1, IF: 9.4) [PDF]
Pinhan Fu, Xinyan Liang, Tingjin Luo, Qian Guo, Yayu Zhang, Yuhua Qian#. Core-Structures-Guided Multi-Modal Classification Neural Architecture Search. The 33rd International Joint Conference on Artificial Intelligence, pp. 3980-3988, 2024. (CCF A)
Zhangqi Jiang, Tingjin Luo#, Xinyan Liang. Deep Incomplete Multi-View Learning Network with Insufficient Label Information, 38th AAAI Conference on Artificial Intelligence (AAAI-24), Accepted. (CCF A) [PDF]
Hong Tao, Jiacheng Jiang, Chenping Hou#, Tingjin Luo, Ruidong Fan, Jing Zhang, Compound Weakly Supervised Clustering, IEEE Transactions on Image Processing, 2024, 33(1): 957 - 971. (JCR Q1, CCF A, IF: 10.8) [PDF]
周浩，罗廷金#，崔国恒. 结合对象属性识别的图像场景图生成方法研究. 计算机科学, 2024, 51（11）： 205-212. (CCF T2级中文期刊)
周浩，王超，崔国恒，罗廷金#.基于多语义关联与融合的视觉问答模型. 计算机应用, 2024, 录用. (CCF T2级中文期刊)
Xinyue Zhang, Tingjin Luo#, Yueying Liu, Chenping Hou. Imbalanced Multi-instance Multi-label Learning via Coding Ensemble and Adaptive Thresholds. The 32nd ACM International Conference on Multimedia, October 28 - November 1, 2024, Melbourne , VIC , Australia, 2024, Association for Computing Machinery, New York, NY, USA, 5413–5422.[PDF] (CCF A类会议)
Quanjiang Li, Tingjin Luo#, Mingdie Jiang, Jiahui Liao, Zhangqi Jiang. Deep Incomplete Multi-View Network Semi-Supervised Multi-Label Learning with Unbiased Loss. The 32nd ACM International Conference on Multimedia, October 28 - November 1, 2024, Melbourne, VIC , Australia, 2024, Association for Computing Machinery, New York, NY, USA, 9048–9056. [PDF] (CCF A类会议)
Hao Zhou, Jun Zhang#, Tingjin Luo#, Yazhou Yang, Jun Lei, Debiased Scene Graph Generation for Dual Imbalance Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 4, pp. 4274-4288, 1 April 2023. (JCR Q1, CCF A, IF: 24.314) [PDF][CODE]
Xinyue Dong, Tingjin Luo#, Ruidong Fan, Wenzhang Zhuge, Chenping Hou#, Active Label Distribution Learning via Kernel Maximum Mean Discrepancy, Frontiers of Computer Science, 2023, 17(4): 174327. (JCR Q2, CCF B, CCF T1, IF: 2.669) [PDF]
Ningzhao Sun*, Tingjin Luo*, Hong Tao, Chenping Hou#, Dewen Hu#, Semi-supervised Learning with Label Proportion, IEEE Transactions on Knowledge and Data Engineering, vol. 35, no. 1, pp. 877-890, 1 Jan. 2023. (CCF A, IF: 9.235) [PDF]
Yueying Liu, Tingjin Luo#. Joint Distribution Alignment and Transfer Subspace Learning for Unsupervised Domain Adaptation. IEEE 9th International Conference on Cloud Computing and Intelligence Systems, Dali, China, 2023, pp. 53-58, doi: 10.1109/CCIS59572.2023.10262974.
Shilin Gu, Tingjin Luo, Ming He, and Chenping Hou, Online Learning with Incremental Feature Space and Bandit Feedback, IEEE Transactions on Knowledge and Data Engineering, 2023, Accepted. (CCF A, IF: 9.235) [PDF]
Ruidong Fan, Xiao Ouyang, Tingjin Luo, Dewen Hu, Chenping Hou. Incomplete Multi-view Learning under Label Shift. IEEE Transactions on Image Processing, 2023.06, Accepted. (JCR Q1, CCF A, IF: 11.041) [PDF]
Xiuqi Huang, Haotian Ni, Tingjin Luo, Hong Tao, Chenping Hou#, Decorrelated Spectral Regression: An Unsupervised Dimension Reduction Method under Data Selection Bias, Neurocomputing, Volume 549, 7 September 2023, 126406. (JCR Q2, IF: 5.779) [PDF]
Jing Zhang, Hong Tao#, Tingjin Luo, Chenping Hou#, Safe Incomplete Label Distribution Learning, Pattern Recognition, Volume 125, May 2022, 108518. (JCR Q1, CCF B, IF: 8.518) [PDF]
Wenzhang Zhuge, Hong Tao, Tingjin Luo#, Linli Zeng, Chenping Hou#, Dongyun Yi, Joint Representation Learning and Clustering: A Framework for Grouping Partial Multiview Data, IEEE Transactions on Knowledge and Data Engineering, 34(8): 3826 - 3840, 2022.08.01, DOI: 10.1109/TKDE.2020.3028422. (CCF A, IF: 9.235) [PDF]
Xijia Tang, Chao Xu, Tingjin Luo, Chenping Hou#. Multi-instance positive and unlabeled learning with bi-level embedding, Intelligent Data Analysis, 26(3): 659-678, 2022.
Hao Zhou, Yazhou Yang, Tingjin Luo#, Jun Zhang#, Jun Lei, Shuohao Li, A Unified Deep Sparse Graph Attention Network for Scene Graph Generation, Pattern Recognition, 2021, Accepted. (JCR Q1, CCF B, IF: 8.518) [PDF]
Hao Zhou, Tingjin Luo#, Jun Zhang, Jun Lei, Shuohao Li, Relationship-aware Primal-Dual Graph Attention Network for Scene Graph Generation, in IEEE International Conference on Multimedia and Expo (ICME), Shenzhen, China, July 5-9, 2021, Accepted. (CCF B) [PDF]
Xijia Tang, Tingjin Luo#, Tianxiang Luan, Chenping Hou, Multiple Instance Learning for Unilateral Data, in Proceedings of Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2021), Accepted, Delhi, India, 2021. (CCF C) [PDF]
Xinyue Dong, Shilin Gu, Wenzhang Zhuge, Tingjin Luo, Chenping Hou#, Active Label Distribution Learning, Neurocomputing, vol. 436, pp. 12-21, 2021, DOI: 10.1016/j.neucom.2020.12.128. (JCR Q1, CCF B, IF: 5.779) [PDF]
诸葛文章，范瑞东，罗廷金，陶红，侯臣平，基于独立自表达学习的不完全多视图聚类方法，中国科学: 信息科学, 录用. (CCFA类中文期刊，SCI检索)
Ruidong Fan, Tingjin Luo, Wenzhang Zhuge, Sheng Qiang, Chenping Hou#, Multi-view Subspace Learning via Bidirectional Sparsity, Pattern Recognition, 108: 107524, 2020, DOI: 10.1016/j.patcog.2020.107524, (JCR Q1, CCF B, IF: 8.518). [PDF][Code]
Tianxiang Luan, Tingjin Luo, Wenzhang Zhuge, Chenping Hou#, Optimal Representative Distribution Margin Machine for Multi-Instance Learning, IEEE Access, vol. 8, pp. 74864-74874, 2020, DOI: 10.1109/ACCESS.2020.2988764. (IF: 3.745). [PDF]
Wenzhang Zhuge, Tingjin Luo, Hong Tao, Chenping Hou#, Dongyun Yi, Multi-View Spectral Clustering With Incomplete Graphs, IEEE Access, vol. 8, pp. 99820-99831, 2020, DOI: 10.1109/ACCESS.2020.2997755. (IF: 3.745) [PDF]
Tingjin Luo, Chenping Hou#, Feiping Nie, Dongyun Yi, Dimension Reduction for Non-Gaussian Data by Adaptive Discriminative Analysis, IEEE Transactions on Cybernetics, vol. 49, no. 3, pp. 933-946, March 2019, DOI: 10.1109/TCYB.2018.2789524. (JCR Q1, IF: 19.118) [PDF][CODE]
Zhipeng Lin, Zhenyu Zhao, Tingjin Luo#, Wenjing Yang, Yongjun Zhang, Yuhua Tang, Non-Convex Transfer Subspace Learning for Unsupervised Domain Adaptation, Proceedings of IEEE International Conference on Multimedia and Expo (ICME 2019), Shanghai, China, 2019, pp. 1468-1473, DOI: 10.1109/ICME.2019.00254, EI: 20193407349323. (CCF B) [PDF]
Haotian Wang, Wenjing Yang#, Zhenyu Zhao, Tingjin Luo, Ji Wang, Yuhua Tang, Rademacher Dropout: An Adaptive Dropout for Deep Neural Network via Optimizing Generalization Gap, Neurocomputing, vol. 357, pp. 177-187, 2019, DOI: 10.1016/j.neucom.2019.05.008. (JCR Q1, CCF B, IF: 5.779) [PDF]
Haodong Yang, Jun Zhang#, Shuohao Li#, Tingjin Luo, Bi-direction Hierarchical LSTM with Spatial-Temporal Attention for Action Recognition, Journal of Intelligent & Fuzzy Systems, vol.36, no. 1, pp. 775-786, 2019, DOI: 10.3233/JIFS-18209. (IF: 1.851) [PDF]
Tingjin Luo, Chenping Hou#, Feiping Nie, Hong Tao, Dongyun Yi, Semi-Supervised Feature Selection via Insensitive Sparse Regression with Application to Video Semantic Recognition, IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 10, pp. 1943-1956, 2018, DOI: 10.1109/TKDE.2018.2810286, WOS:000444603900009. (CCF A, IF: 9.235) [PDF]
Weizhong Zhang*, Tingjin Luo*, Shuang Qiu, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang#, Identifying Genetic Risk Factors for Alzheimer’s Disease via Shared Tree-Guided Feature Learning Across Multiple Tasks, IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 11, pp. 2145-2156, 2018, DOI: 10.1109/TKDE.2018.2816029, WOS:000446795900010. (CCF A, IF: 9.235) [PDF]
Gongmin Lan, Chenping Hou#, Feiping Nie, Tingjin Luo, Dongyun Yi, Robust Feature Selection via Simultaneous Capped Norm and Sparse Regularizer Minimization, Neurocomputing, vol. 283, pp. 228-240, 2018, DOI: 10.1016/j.neucom.2017.12.055, WOS:000424896600021. (JCR Q1, CCF B, IF: 5.779) [PDF]
Tingjin Luo, Weizhong Zhang, Shuang Qiu, Yang Yang, Dongyun Yi, Guangtao Wang, Jieping Ye#, Jie Wang#, Functional Annotation of Human Protein Coding Isoforms via Non-convex Multi-Instance Learning, Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2017), Halifax, Canada, August 2017, pp. 345-354. (CCF A) [PDF]
Yang Yang*, Tingjin Luo*, Zhoujun Li, Xiaoming Zhang, Philip S. Yu, A Robust Method for Inferring Network Structures, Scientific Reports, vol. 7, no. 5221, pp. 1-12, 2017, DOI: 10.1038/s41598-017-04725-2, WOS:000405425000025. (JCR Q2, IF: 4.576)[PDF]
Chenping Hou, Yuanyuan Jiao, Feiping Nie, Tingjin Luo, Zhi-Hua Zhou#, 2D Feature Selection by Sparse Matrix Regression. IEEE Transations on Image Processing, vol. 26, no. 9, pp. 4255-4268, 2017, DOI: 10.1109/TIP.2017.2713948, WOS:000405395900001. (CCF A, IF: 9.340) [PDF]
Guangtao Wang, Jiayu Zhou, Jingjie Ni, Tingjin Luo, Wei Long, Hai Zhen, Gao Cong, Jieping Ye#, Robust Self-Tuning Sparse Subspace Clustering, Procedings of 17th IEEE International Conference on Data Mining Workshops (ICDMW 2017), pp.858-865, New Orleans, USA, 2017, DOI: 10.1109/ICDMW.2017.117, WOS:000425845700114. [PDF]
Tingjin Luo, Chenping Hou#, Dongyun Yi, Jun Zhang, Discriminative Orthogonal Elastic Preserving Projections for Classification, Neurocomputing, vol. 179, pp. 54-68, 2016, DOI: 10.1016/j.neucom.2015.11.037, WOS:000370090300005. (JCR Q1, CCF B, IF: 5.779) [PDF]
Tingjin Luo, Jun Zhang, Lin Lian, Speed up Junction Detector based on Azimuth Consensus by Harris Corner, Optical Review, vol. 21, no. 2, pp. 135-142, Mar. 2014, DOI: 10.1007/s10043-014-0021-1, WOS:000334253000005. (IF: )
Jun Zhang, Tingjin Luo#, Gui Gao, Lin Lian, Junction Point Detection Algorithm for SAR Image, International Journal of Antennas and Propagation, vol. 2013, pp. 1-9, Mar. 2013, DOI: 10.1155/2013/357379, WOS:000317567100001. (IF: 1.207) [PDF]
Jun Zhang, Weiqiang Huang, Tingjin Luo, 3D Reconstruction of Periodic Human Walking Trajectories Based on Single View, Chinese Journal of Electronics, vol. 22, no. 3, pp.455-460, July 2013, WOS:000321481000004. (JCR Q4, IF: 0.941)
Jun Zhang, Shukui Xu, Kuihua Huang, Tingjin Luo, Accurate Moving Target Detection Based on Background Subtraction and SUSAN, International Journal of Computer and Electrical Engineering, vol. 4, no. 4, pp.436-439, Aug. 2012, DOI: 10.7763/IJCEE.2012.V4.529, WOS:000321481000004. [PDF]