Tingjin Luo

According to our database, Tingjin Luo authored at least 64 papers between 2016 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Correcting Visual Blur Induced by Attention Distraction to Reduce Hallucinations: Algorithm and Theory.

Quanjiang Li, Zhiming Liu, Wei Luo, Tingjin Luo, Chenping Hou

CoRR, May, 2026

Adaptive Disentangled Representation Learning for Incomplete Multi-View Multi-Label Classification.

Quanjiang Li, Zhiming Liu, Tianxiang Xu, Tingjin Luo, Chenping Hou

CoRR, January, 2026

Non-Convex Transfer Subspace Learning via Embedded Distribution Alignment.

Tingjin Luo, Yueying Liu, Xinyue Zhang, Chenping Hou

IEEE Trans. Image Process., 2026

NLSC: A noise-robust label shift correction framework via three-head training and class-adaptive cleaning.

Xiaowen Wu, Ruidong Fan, Tingjin Luo, Chenping Hou

Inf. Sci., 2026

A reliable framework for brain tumor segmentation via multi-modal fusion and uncertainty modeling.

Tongxue Zhou, Mingyang Li, Su Ruan, Tingjin Luo, Bingbing Jiang, Junan Zhu, Ping Ma, Defu Yang, Guang Yang

Inf. Fusion, 2026

UTriGate-Net : Uncertainty-aware brain tumor segmentation via triaxial context encoding and gated modality fusion.

Tongxue Zhou, Su Ruan, Yanda Meng, Jinming Duan, Haigen Hu, Bingbing Jiang, Zhiwei Ji, Bangli Liu, Tingjin Luo, Baiying Lei

Expert Syst. Appl., 2026

A hierarchical teacher-student learning framework with adaptive cross-modal fusion for brain tumor segmentation.

Tongxue Zhou, Su Ruan, Jinming Duan, Haigen Hu, Yanda Meng, Ling Huang, Defu Yang, Bingbing Jiang, Tingjin Luo, Zhiwei Ji, Baiying Lei

Expert Syst. Appl., 2026

CLASS: Deep Partial Label Feature Selection with Cluster-Guided Disambiguation and Structured Sparsity.

Tingjin Luo, Mengyuan Tong, Qingyang Shu, Yueying Liu, Hao Zhou, Zhen Wang

Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1, 2026

ESTIM: Efficient and Scalable Tensorial Incomplete Multi-view Semi-supervised Classification.

Tingjin Luo, XiangYao Li, Zhangqi Jiang, Shuanghui Zhang, Dewen Hu

Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1, 2026

DPRM: A Dual Implicit Process Reward Model in Multi-Hop Question Answering.

Xinyi Wang, Yiping Song, Zhiliang Tian, Bo Liu, Tingjin Luo, Minlie Huang

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

Multi-Label Classification with Incremental and Decremental Features.

Mingdie Jiang, Quanjiang Li, Tingjin Luo, Yiping Song, Chenping Hou

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Adversarial Graph Fusion for Incomplete Multi-view Semi-supervised Learning with Tensorial Imputation.

Zhangqi Jiang, Tingjin Luo, Xu Yang, Xinyan Liang

CoRR, September, 2025

Exploring the Essence of Relationships for Scene Graph Generation via Causal Features Enhancement Network.

Hao Zhou, Tingjin Luo, Jun Zhang, Liguo Liu

IEEE Trans. Pattern Anal. Mach. Intell., August, 2025

Imbalanced multi-instance multi-label learning via tensor product-based semantic fusion.

Xinyue Zhang, Tingjin Luo

Frontiers Comput. Sci., August, 2025

Nonconvex and discriminative transfer subspace learning for unsupervised domain adaptation.

Yueying Liu, Tingjin Luo

Frontiers Comput. Sci., February, 2025

Noise-free prototype guided representation calibration under label noise.

Huiting Yuan, Tingjin Luo, Xinghao Wu, Jie Jiang

Knowl. Based Syst., 2025

Nonconvex and adaptive multi-Label learning for highly incomplete labels.

Tingjin Luo, Quanjiang Liang, Mingdie Jiang, Chenping Hou

Knowl. Based Syst., 2025

A forward k-means algorithm for regression clustering.

Jun Lu, Tingjin Luo, Kai Li

Inf. Sci., 2025

Dynamic collaborative learning with heterogeneous knowledge transfer for long-tailed visual recognition.

Hao Zhou, Tingjin Luo, Yongming He

Inf. Fusion, 2025

Improving Evolutionary Multi-View Classification via Eliminating Individual Fitness Bias.

Xinyan Liang, Shuai Li, Qian Guo, Yuhua Qian, Bingbing Jiang, Tingjin Luo, Liang Du

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Theory-Driven Label-Specific Representation for Incomplete Multi-View Multi-Label Learning.

Quanjiang Li, Tianxiang Xu, Tingjin Luo, Yan Zhong, Yang Li, Yiyun Zhou, Chenping Hou

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

One-step Label Shift Adaptation via Robust Weight Estimation.

Ruidong Fan, Xiao Ouyang, Tingjin Luo, Lijun Zhang, Chenping Hou

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

Trusted Multi-View Classification with Expert Knowledge Constraints.

Xinyan Liang, Shijie Wang, Yuhua Qian, Qian Guo, Liang Du, Bingbing Jiang, Tingjin Luo, Feijiang Li

Proceedings of the Forty-second International Conference on Machine Learning, 2025

DCMKC: A Dual Consistency Matching Approach for Multi-hop Question Answering in LLMs.

Xinyi Wang, Yiping Song, Chang Liu, Tingjin Luo, Bo Liu, Zheng Xie, Minlie Huang

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

Theory-Inspired Deep Multi-View Multi-Label Learning with Incomplete Views and Noisy Labels.

Quanjiang Li, Tingjin Luo, Jiahui Liao

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Core-to-Global Reasoning for Compositional Visual Question Answering.

Hao Zhou, Tingjin Luo, Zhangqi Jiang

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

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

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Absent Multiview Semisupervised Classification.

Wenzhang Zhuge, Tingjin Luo, Ruidong Fan, Hong Tao, Chenping Hou, Dongyun Yi

IEEE Trans. Cybern., March, 2024

Robust discriminative feature learning with calibrated data reconstruction and sparse low-rank model.

Tingjin Luo, Yang Yang, Dongyun Yi, Jieping Ye

Appl. Intell., February, 2024

Compound Weakly Supervised Clustering.

Hong Tao, Jiacheng Jiang, Chenping Hou, Tingjin Luo, Ruidong Fan, Jing Zhang

IEEE Trans. Image Process., 2024

Imbalanced Multi-instance Multi-label Learning via Coding Ensemble and Adaptive Thresholds.

Xinyue Zhang, Tingjin Luo, Yueying Liu, Chenping Hou

Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

Deep Incomplete Multi-View Network Semi-Supervised Multi-Label Learning with Unbiased Loss.

Quanjiang Li, Tingjin Luo, Mingdie Jiang, Jiahui Liao, Zhangqi Jiang

Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

Core-Structures-Guided Multi-Modal Classification Neural Architecture Search.

Pinhan Fu, Xinyan Liang, Tingjin Luo, Qian Guo, Yayu Zhang, Yuhua Qian

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Deep Incomplete Multi-View Learning Network with Insufficient Label Information.

Zhangqi Jiang, Tingjin Luo, Xinyan Liang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Online Learning With Incremental Feature Space and Bandit Feedback.

Shilin Gu, Tingjin Luo, Ming He, Chenping Hou

IEEE Trans. Knowl. Data Eng., December, 2023

Decorrelated spectral regression: An unsupervised dimension reduction method under data selection bias.

Xiuqi Huang, Haotian Ni, Tingjin Luo, Hong Tao, Chenping Hou

Neurocomputing, September, 2023

Active label distribution learning via kernel maximum mean discrepancy.

Xinyue Dong, Tingjin Luo, Ruidong Fan, Wenzhang Zhuge, Chenping Hou

Frontiers Comput. Sci., August, 2023

Debiased Scene Graph Generation for Dual Imbalance Learning.

Hao Zhou, Jun Zhang, Tingjin Luo, Yazhou Yang, Jun Lei

IEEE Trans. Pattern Anal. Mach. Intell., April, 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

Incomplete Multi-View Learning Under Label Shift.

Ruidong Fan, Xiao Ouyang, Tingjin Luo, Dewen Hu, Chenping Hou

IEEE Trans. Image Process., 2023

Joint Distribution Alignment and Transfer Subspace Learning for Unsupervised Domain Adaptation.

Yueying Liu, Tingjin Luo

Proceedings of the 9th IEEE International Conference on Cloud Computing and Intelligent Systems, 2023

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

A unified deep sparse graph attention network for scene graph generation.

Hao Zhou, Yazhou Yang, Tingjin Luo, Jun Zhang, Shuohao Li

Pattern Recognit., 2022

Safe incomplete label distribution learning.

Jing Zhang, Hong Tao, Tingjin Luo, Chenping Hou

Pattern Recognit., 2022

Multi-instance positive and unlabeled learning with bi-level embedding.

Xijia Tang, Chao Xu, Tingjin Luo, Chenping Hou

Intell. Data Anal., 2022

2021

Active label distribution learning.

Xinyue Dong, Shilin Gu, Wenzhang Zhuge, Tingjin Luo, Chenping Hou

Neurocomputing, 2021

Multiple Instance Learning for Unilateral Data.

Xijia Tang, Tingjin Luo, Tianxiang Luan, Chenping Hou

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

Relationship-Aware Primal-Dual Graph Attention Network For Scene Graph Generation.

Hao Zhou, Tingjin Luo, Jun Zhang, Jun Lei, Shuohao Li

Proceedings of the 2021 IEEE International Conference on Multimedia and Expo, 2021

2020

Multi-view subspace learning via bidirectional sparsity.

Ruidong Fan, Tingjin Luo, Wenzhang Zhuge, Sheng Qiang, Chenping Hou

Pattern Recognit., 2020

Multi-View Spectral Clustering With Incomplete Graphs.

Wenzhang Zhuge, Tingjin Luo, Hong Tao, Chenping Hou, Dongyun Yi

IEEE Access, 2020

Optimal Representative Distribution Margin Machine for Multi-Instance Learning.

Tianxiang Luan, Tingjin Luo, Wenzhang Zhuge, Chenping Hou

IEEE Access, 2020

2019

Dimension Reduction for Non-Gaussian Data by Adaptive Discriminative Analysis.

Tingjin Luo, Chenping Hou, Feiping Nie, Dongyun Yi

IEEE Trans. Cybern., 2019

Bi-direction hierarchical LSTM with spatial-temporal attention for action recognition.

Haodong Yang, Jun Zhang, Shuohao Li, Tingjin Luo

J. Intell. Fuzzy Syst., 2019

Rademacher dropout: An adaptive dropout for deep neural network via optimizing generalization gap.

Haotian Wang, Wenjing Yang, Zhenyu Zhao, Tingjin Luo, Ji Wang, Yuhua Tang

Neurocomputing, 2019

Non-Convex Transfer Subspace Learning for Unsupervised Domain Adaptation.

Zhipeng Lin, Zhenyu Zhao, Tingjin Luo, Wenjing Yang, Yongjun Zhang, Yuhua Tang

Proceedings of the IEEE International Conference on Multimedia and Expo, 2019

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, Xiaofei He, Jie Wang

IEEE Trans. Knowl. Data Eng., 2018

Semi-Supervised Feature Selection via Insensitive Sparse Regression with Application to Video Semantic Recognition.

Tingjin Luo, Chenping Hou, Feiping Nie, Hong Tao, Dongyun Yi

IEEE Trans. Knowl. Data Eng., 2018

Robust feature selection via simultaneous sapped norm and sparse regularizer minimization.

Gongmin Lan, Chenping Hou, Feiping Nie, Tingjin Luo, Dongyun Yi

Neurocomputing, 2018

2017

2D Feature Selection by Sparse Matrix Regression.

Chenping Hou, Yuanyuan Jiao, Feiping Nie, Tingjin Luo, Zhi-Hua Zhou

IEEE Trans. Image Process., 2017

Nonconvex One-bit Single-label Multi-label Learning.

Shuang Qiu, Tingjin Luo, Jieping Ye, Ming Lin

CoRR, 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

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Robust Self-Tuning Sparse Subspace Clustering.

Guangtao Wang, Jiayu Zhou, Jingjie Ni, Tingjin Luo, Wei Long, Hai Zhen, Gao Cong, Jieping Ye

Proceedings of the 2017 IEEE International Conference on Data Mining Workshops, 2017

2016

Discriminative orthogonal elastic preserving projections for classification.

Tingjin Luo, Chenping Hou, Dongyun Yi, Jun Zhang

Neurocomputing, 2016