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ORCIDTingjin Luo
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2020 – today
- 2025
[j27]Yueying Liu, Tingjin Luo:
Nonconvex and discriminative transfer subspace learning for unsupervised domain adaptation. Frontiers Comput. Sci. 19(2): 192307 (2025)- [j26]Hao Zhou
, Tingjin Luo, Yongming He:
Dynamic collaborative learning with heterogeneous knowledge transfer for long-tailed visual recognition. Inf. Fusion 115: 102734 (2025) - 2024
- [j25]Tingjin Luo, Yang Yang, Dongyun Yi, Jieping Ye:
Robust discriminative feature learning with calibrated data reconstruction and sparse low-rank model. Appl. Intell. 54(3): 2867-2880 (2024) - [j24]Wenzhang Zhuge, Tingjin Luo, Ruidong Fan, Hong Tao, Chenping Hou, Dongyun Yi:
Absent Multiview Semisupervised Classification. IEEE Trans. Cybern. 54(3): 1708-1721 (2024) - [j23]Hong Tao, Jiacheng Jiang, Chenping Hou, Tingjin Luo, Ruidong Fan, Jing Zhang:
Compound Weakly Supervised Clustering. IEEE Trans. Image Process. 33: 957-971 (2024) - [c10]Zhangqi Jiang, Tingjin Luo, Xinyan Liang:
Deep Incomplete Multi-View Learning Network with Insufficient Label Information. AAAI 2024: 12919-12927 - [c9]Pinhan Fu, Xinyan Liang, Tingjin Luo, Qian Guo, Yayu Zhang, Yuhua Qian:
Core-Structures-Guided Multi-Modal Classification Neural Architecture Search. IJCAI 2024: 3980-3988 - [c8]Xinyue Zhang, Tingjin Luo, Yueying Liu, Chenping Hou:
Imbalanced Multi-instance Multi-label Learning via Coding Ensemble and Adaptive Thresholds. ACM Multimedia 2024: 5413-5422 - [c7]Quanjiang Li, Tingjin Luo, Mingdie Jiang, Jiahui Liao, Zhangqi Jiang:
Deep Incomplete Multi-View Network Semi-Supervised Multi-Label Learning with Unbiased Loss. ACM Multimedia 2024: 9048-9056 - [i2]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. CoRR abs/2411.16724 (2024) - 2023
- [j22]Xinyue Dong, Tingjin Luo, Ruidong Fan, Wenzhang Zhuge, Chenping Hou:
Active label distribution learning via kernel maximum mean discrepancy. Frontiers Comput. Sci. 17(4): 174327 (2023) - [j21]Xiuqi Huang, Haotian Ni, Tingjin Luo, Hong Tao, Chenping Hou:
Decorrelated spectral regression: An unsupervised dimension reduction method under data selection bias. Neurocomputing 549: 126406 (2023) - [j20]Hao Zhou, Jun Zhang, Tingjin Luo, Yazhou Yang, Jun Lei:
Debiased Scene Graph Generation for Dual Imbalance Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 4274-4288 (2023) - [j19]Ruidong Fan, Xiao Ouyang, Tingjin Luo, Dewen Hu, Chenping Hou:
Incomplete Multi-View Learning Under Label Shift. IEEE Trans. Image Process. 32: 3702-3716 (2023) - [j18]Ningzhao Sun, Tingjin Luo, Wenzhang Zhuge, Hong Tao, Chenping Hou, Dewen Hu:
Semi-Supervised Learning With Label Proportion. IEEE Trans. Knowl. Data Eng. 35(1): 877-890 (2023) - [j17]Shilin Gu, Tingjin Luo, Ming He, Chenping Hou:
Online Learning With Incremental Feature Space and Bandit Feedback. IEEE Trans. Knowl. Data Eng. 35(12): 12902-12916 (2023) - [c6]Yueying Liu, Tingjin Luo:
Joint Distribution Alignment and Transfer Subspace Learning for Unsupervised Domain Adaptation. CCIS 2023: 53-58 - 2022
- [j16]Xijia Tang, Chao Xu, Tingjin Luo, Chenping Hou:
Multi-instance positive and unlabeled learning with bi-level embedding. Intell. Data Anal. 26(3): 659-678 (2022) - [j15]Hao Zhou, Yazhou Yang, Tingjin Luo, Jun Zhang, Shuohao Li:
A unified deep sparse graph attention network for scene graph generation. Pattern Recognit. 123: 108367 (2022) - [j14]Jing Zhang, Hong Tao, Tingjin Luo, Chenping Hou:
Safe incomplete label distribution learning. Pattern Recognit. 125: 108518 (2022) - [j13]Wenzhang Zhuge, Hong Tao, Tingjin Luo, Ling-Li Zeng, Chenping Hou, Dongyun Yi:
Joint Representation Learning and Clustering: A Framework for Grouping Partial Multiview Data. IEEE Trans. Knowl. Data Eng. 34(8): 3826-3840 (2022) - 2021
- [j12]Xinyue Dong, Shilin Gu, Wenzhang Zhuge, Tingjin Luo, Chenping Hou:
Active label distribution learning. Neurocomputing 436: 12-21 (2021) - [c5]Hao Zhou, Tingjin Luo, Jun Zhang, Jun Lei, Shuohao Li:
Relationship-Aware Primal-Dual Graph Attention Network For Scene Graph Generation. ICME 2021: 1-6 - [c4]Xijia Tang, Tingjin Luo, Tianxiang Luan, Chenping Hou:
Multiple Instance Learning for Unilateral Data. PAKDD (1) 2021: 590-602 - 2020
- [j11]Tianxiang Luan, Tingjin Luo, Wenzhang Zhuge, Chenping Hou:
Optimal Representative Distribution Margin Machine for Multi-Instance Learning. IEEE Access 8: 74864-74874 (2020) - [j10]Wenzhang Zhuge, Tingjin Luo, Hong Tao, Chenping Hou, Dongyun Yi:
Multi-View Spectral Clustering With Incomplete Graphs. IEEE Access 8: 99820-99831 (2020) - [j9]Ruidong Fan, Tingjin Luo, Wenzhang Zhuge, Sheng Qiang, Chenping Hou:
Multi-view subspace learning via bidirectional sparsity. Pattern Recognit. 108: 107524 (2020)
2010 – 2019
- 2019
- [j8]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 357: 177-187 (2019) - [j7]Haodong Yang, Jun Zhang, Shuohao Li, Tingjin Luo:
Bi-direction hierarchical LSTM with spatial-temporal attention for action recognition. J. Intell. Fuzzy Syst. 36(1): 775-786 (2019) - [j6]Tingjin Luo, Chenping Hou, Feiping Nie, Dongyun Yi:
Dimension Reduction for Non-Gaussian Data by Adaptive Discriminative Analysis. IEEE Trans. Cybern. 49(3): 933-946 (2019) - [c3]Zhipeng Lin, Zhenyu Zhao, Tingjin Luo, Wenjing Yang, Yongjun Zhang, Yuhua Tang:
Non-Convex Transfer Subspace Learning for Unsupervised Domain Adaptation. ICME 2019: 1468-1473 - 2018
- [j5]Gongmin Lan, Chenping Hou, Feiping Nie, Tingjin Luo, Dongyun Yi:
Robust feature selection via simultaneous sapped norm and sparse regularizer minimization. Neurocomputing 283: 228-240 (2018) - [j4]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 Trans. Knowl. Data Eng. 30(10): 1943-1956 (2018) - [j3]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 Trans. Knowl. Data Eng. 30(11): 2145-2156 (2018) - 2017
- [j2]Chenping Hou, Yuanyuan Jiao, Feiping Nie, Tingjin Luo, Zhi-Hua Zhou:
2D Feature Selection by Sparse Matrix Regression. IEEE Trans. Image Process. 26(9): 4255-4268 (2017) - [c2]Guangtao Wang, Jiayu Zhou, Jingjie Ni, Tingjin Luo, Wei Long, Hai Zhen, Gao Cong, Jieping Ye:
Robust Self-Tuning Sparse Subspace Clustering. ICDM Workshops 2017: 858-865 - [c1]Tingjin Luo, Weizhong Zhang, Shang Qiu, Yang Yang, Dongyun Yi, Guangtao Wang, Jieping Ye, Jie Wang:
Functional Annotation of Human Protein Coding Isoforms via Non-convex Multi-Instance Learning. KDD 2017: 345-354 - [i1]Shuang Qiu, Tingjin Luo, Jieping Ye, Ming Lin:
Nonconvex One-bit Single-label Multi-label Learning. CoRR abs/1703.06104 (2017) - 2016
- [j1]Tingjin Luo, Chenping Hou, Dongyun Yi, Jun Zhang:
Discriminative orthogonal elastic preserving projections for classification. Neurocomputing 179: 54-68 (2016)
Coauthor Index
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