Discriminative orthogonal elastic preserving projections for classification. - Tingjin Luo; Chenping Hou; Dongyun Yi; Jun Zhang 067 (Neurocomputing, 2016)

Robust Self-Tuning Sparse Subspace Clustering. - Guangtao Wang; Jiayu Zhou; Jingjie Ni; Tingjin Luo; Wei Long; Hai Zhen; Gao Cong; Jieping Ye (ICDM Workshops, 2017)

Functional Annotation of Human Protein Coding Isoforms via Non-convex Multi-Instance Learning. - Tingjin Luo; Weizhong Zhang; Shang Qiu; Yang Yang; Dongyun Yi; Guangtao Wang; Jieping Ye; Jie Wang 005 (KDD, 2017)

Nonconvex One-bit Single-label Multi-label Learning. - Shuang Qiu; Tingjin Luo; Jieping Ye; Ming Lin (CoRR, 2017)

2D Feature Selection by Sparse Matrix Regression. - Chenping Hou; Yuanyuan Jiao; Feiping Nie 001; Tingjin Luo; Zhi-Hua Zhou (IEEE Trans. Image Process., 2017)

Robust feature selection via simultaneous sapped norm and sparse regularizer minimization. - Gongmin Lan; Chenping Hou; Feiping Nie 001; Tingjin Luo; Dongyun Yi (Neurocomputing, 2018)

Semi-Supervised Feature Selection via Insensitive Sparse Regression with Application to Video Semantic Recognition. - Tingjin Luo; Chenping Hou; Feiping Nie 001; Hong Tao; Dongyun Yi (IEEE Trans. Knowl. Data Eng., 2018)

Identifying Genetic Risk Factors for Alzheimer's Disease via Shared Tree-Guided Feature Learning Across Multiple Tasks. - Weizhong Zhang; Tingjin Luo; Shuang Qiu; Jieping Ye; Deng Cai 001; Xiaofei He 001; Jie Wang 005 (IEEE Trans. Knowl. Data Eng., 2018)

Non-Convex Transfer Subspace Learning for Unsupervised Domain Adaptation. - Zhipeng Lin; Zhenyu Zhao; Tingjin Luo; Wenjing Yang 002; Yongjun Zhang 006; Yuhua Tang (ICME, 2019)

Rademacher dropout: An adaptive dropout for deep neural network via optimizing generalization gap. - Haotian Wang 001; Wenjing Yang 002; Zhenyu Zhao; Tingjin Luo; Ji Wang 001; Yuhua Tang (Neurocomputing, 2019)

Bi-direction hierarchical LSTM with spatial-temporal attention for action recognition. - Haodong Yang; Jun Zhang 067; Shuohao Li; Tingjin Luo (J. Intell. Fuzzy Syst., 2019)

Dimension Reduction for Non-Gaussian Data by Adaptive Discriminative Analysis. - Tingjin Luo; Chenping Hou; Feiping Nie 001; Dongyun Yi (IEEE Trans. Cybern., 2019)

Optimal Representative Distribution Margin Machine for Multi-Instance Learning. - Tianxiang Luan; Tingjin Luo; Wenzhang Zhuge; Chenping Hou (IEEE Access, 2020)

Multi-View Spectral Clustering With Incomplete Graphs. - Wenzhang Zhuge; Tingjin Luo; Hong Tao; Chenping Hou; Dongyun Yi (IEEE Access, 2020)

Multi-view subspace learning via bidirectional sparsity. - Ruidong Fan; Tingjin Luo; Wenzhang Zhuge; Sheng Qiang; Chenping Hou (Pattern Recognit., 2020)

Relationship-Aware Primal-Dual Graph Attention Network For Scene Graph Generation. - Hao Zhou 029; Tingjin Luo; Jun Zhang 067; Jun Lei 001; Shuohao Li (ICME, 2021)

Multiple Instance Learning for Unilateral Data. - Xijia Tang; Tingjin Luo; Tianxiang Luan; Chenping Hou (PAKDD (1), 2021)

Active label distribution learning. - Xinyue Dong; Shilin Gu; Wenzhang Zhuge; Tingjin Luo; Chenping Hou (Neurocomputing, 2021)

Multi-instance positive and unlabeled learning with bi-level embedding. - Xijia Tang; Chao Xu 008; Tingjin Luo; Chenping Hou (Intell. Data Anal., 2022)

Safe incomplete label distribution learning. - Jing Zhang 064; Hong Tao; Tingjin Luo; Chenping Hou (Pattern Recognit., 2022)

A unified deep sparse graph attention network for scene graph generation. - Hao Zhou 029; Yazhou Yang; Tingjin Luo; Jun Zhang 067; Shuohao Li (Pattern Recognit., 2022)

Joint Representation Learning and Clustering: A Framework for Grouping Partial Multiview Data. - Wenzhang Zhuge; Hong Tao; Tingjin Luo; Ling-Li Zeng; Chenping Hou; Dongyun Yi (IEEE Trans. Knowl. Data Eng., 2022)

Joint Distribution Alignment and Transfer Subspace Learning for Unsupervised Domain Adaptation. - Yueying Liu; Tingjin Luo (CCIS, 2023)

Incomplete Multi-View Learning Under Label Shift. - Ruidong Fan; Xiao Ouyang; Tingjin Luo; Dewen Hu; Chenping Hou (IEEE Trans. Image Process., 2023)

Semi-Supervised Learning With Label Proportion. - Ningzhao Sun; Tingjin Luo; Wenzhang Zhuge; Hong Tao; Chenping Hou; Dewen Hu (IEEE Trans. Knowl. Data Eng., 2023)

Debiased Scene Graph Generation for Dual Imbalance Learning. - Hao Zhou 029; Jun Zhang 067; Tingjin Luo; Yazhou Yang; Jun Lei 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Active label distribution learning via kernel maximum mean discrepancy. - Xinyue Dong; Tingjin Luo; Ruidong Fan; Wenzhang Zhuge; Chenping Hou (Frontiers Comput. Sci., 2023)

Decorrelated spectral regression: An unsupervised dimension reduction method under data selection bias. - Xiuqi Huang; Haotian Ni; Tingjin Luo; Hong Tao; Chenping Hou (Neurocomputing, 2023)

Online Learning With Incremental Feature Space and Bandit Feedback. - Shilin Gu; Tingjin Luo; Ming He; Chenping Hou (IEEE Trans. Knowl. Data Eng., 2023)

Deep Incomplete Multi-View Learning Network with Insufficient Label Information. - Zhangqi Jiang; Tingjin Luo; Xinyan Liang (AAAI, 2024)

Core-Structures-Guided Multi-Modal Classification Neural Architecture Search. - Pinhan Fu; Xinyan Liang; Tingjin Luo; Qian Guo; Yayu Zhang; Yuhua Qian (IJCAI, 2024)

Deep Incomplete Multi-View Network Semi-Supervised Multi-Label Learning with Unbiased Loss. - Quanjiang Li; Tingjin Luo; Mingdie Jiang; Jiahui Liao; Zhangqi Jiang (ACM Multimedia, 2024)

Imbalanced Multi-instance Multi-label Learning via Coding Ensemble and Adaptive Thresholds. - Xinyue Zhang; Tingjin Luo; Yueying Liu; Chenping Hou (ACM Multimedia, 2024)

Compound Weakly Supervised Clustering. - Hong Tao; Jiacheng Jiang; Chenping Hou; Tingjin Luo; Ruidong Fan; Jing Zhang 064 (IEEE Trans. Image Process., 2024)

Robust discriminative feature learning with calibrated data reconstruction and sparse low-rank model. - Tingjin Luo; Yang Yang; Dongyun Yi; Jieping Ye (Appl. Intell., 2024)

Absent Multiview Semisupervised Classification. - Wenzhang Zhuge; Tingjin Luo; Ruidong Fan; Hong Tao; Chenping Hou; Dongyun Yi (IEEE Trans. Cybern., 2024)

Semi-Supervised Multi-View Multi-Label Learning with View-Specific Transformer and Enhanced Pseudo-Label. - Quanjiang Li; Tingjin Luo; Mingdie Jiang; Zhangqi Jiang; Chenping Hou; Feijiang Li (AAAI, 2025)

Core-to-Global Reasoning for Compositional Visual Question Answering. - Hao Zhou 029; Tingjin Luo; Zhangqi Jiang (AAAI, 2025)

Devils in Middle Layers of Large Vision-Language Models: Interpreting, Detecting and Mitigating Object Hallucinations via Attention Lens. - Zhangqi Jiang; Junkai Chen; Beier Zhu; Tingjin Luo; Yankun Shen; Xu Yang (CVPR, 2025)

Theory-Inspired Deep Multi-View Multi-Label Learning with Incomplete Views and Noisy Labels. - Quanjiang Li; Tingjin Luo; Jiahui Liao (CVPR, 2025)

Dynamic collaborative learning with heterogeneous knowledge transfer for long-tailed visual recognition. - Hao Zhou 029; Tingjin Luo; Yongming He (Inf. Fusion, 2025)

A forward k-means algorithm for regression clustering. - Jun Lu; Tingjin Luo; Kai Li (Inf. Sci., 2025)

Nonconvex and discriminative transfer subspace learning for unsupervised domain adaptation. - Yueying Liu; Tingjin Luo (Frontiers Comput. Sci., 2025)

Imbalanced multi-instance multi-label learning via tensor product-based semantic fusion. - Xinyue Zhang; Tingjin Luo (Frontiers Comput. Sci., 2025)

Exploring the Essence of Relationships for Scene Graph Generation via Causal Features Enhancement Network. - Hao Zhou 029; Tingjin Luo; Jun Zhang 067; Liguo Liu (IEEE Trans. Pattern Anal. Mach. Intell., 2025)