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2020 – today
- 2026
[j9]Zhiqiang Kou
, Haoyuan Xuan, Jingyu Zhu, Hailin Wang, Ming-Kun Xie, Changwei Wang, Jing Wang, Yuheng Jia, Xin Geng:
Tail-Aware Reconstruction of Incomplete Label Distributions With Low-Rank and Sparse Modeling. IEEE Trans. Circuits Syst. Video Technol. 36(2): 1571-1586 (2026)- [i22]Zhiqiang Kou, Junyang Chen, Xin-Qiang Cai, Xiaobo Xia, Ming-Kun Xie, Dong-Dong Wu, Biao Liu, Yuheng Jia, Xin Geng, Masashi Sugiyama, Tat-Seng Chua:
Positive-Unlabeled Reinforcement Learning Distillation for On-Premise Small Models. CoRR abs/2601.20687 (2026) - 2025
- [j8]Chen-Chen Zong, Penghui Yang, Ming-Kun Xie, Sheng-Jun Huang:
A Unified Open Adapter for Open-World Noisy Label Learning: Data-Centric and Learning-Based Insights. IEEE Trans. Circuits Syst. Video Technol. 35(8): 8134-8147 (2025) - [j7]Jing-Cheng Pang, Heng-Bo Fan, Pengyuan Wang, Jiahao Xiao, Nan Tang, Si-Hang Yang, Chengxing Jia, Ming-Kun Xie, Xiang Chen, Sheng-Jun Huang, Yang Yu:
Interactive Large Language Models for Reliable Answering under Incomplete Context. Trans. Mach. Learn. Res. 2025 (2025) - [c20]Lei-Lei Ma, Shuo Xu, Ming-Kun Xie, Lei Wang, Dengdi Sun, Haifeng Zhao:
Correlative and Discriminative Label Grouping for Multi-Label Visual Prompt Tuning. CVPR 2025: 25434-25443 - [c19]Qin-Wen Luo, Ming-Kun Xie, Ye-Wen Wang, Sheng-Jun Huang:
Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL. ICML 2025 - [c18]Zhiqiang Kou, Si Qin, Hailin Wang, Jing Wang, Ming-Kun Xie, Shuo Chen, Yuheng Jia, Tongliang Liu, Masashi Sugiyama, Xin Geng:
Label Distribution Learning with Biased Annotations Assisted by Multi-Label Learning. IJCAI 2025: 5545-5553 - [i21]Zhiqiang Kou, Si Qin, Hailin Wang, Ming-Kun Xie, Shuo Chen, Yuheng Jia, Tongliang Liu, Masashi Sugiyama, Xin Geng:
Label Distribution Learning with Biased Annotations by Learning Multi-Label Representation. CoRR abs/2502.01170 (2025) - [i20]Leilei Ma, Shuo Xu, Ming-Kun Xie, Lei Wang, Dengdi Sun, Haifeng Zhao:
Correlative and Discriminative Label Grouping for Multi-Label Visual Prompt Tuning. CoRR abs/2504.09990 (2025) - [i19]Qin-Wen Luo, Ming-Kun Xie, Ye-Wen Wang, Sheng-Jun Huang:
Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL. CoRR abs/2505.19923 (2025) - [i18]Ming-Kun Xie, Jiahao Xiao, Gang Niu, Lei Feng, Zhiqiang Kou, Min-Ling Zhang, Masashi Sugiyama:
What Makes "Good" Distractors for Object Hallucination Evaluation in Large Vision-Language Models? CoRR abs/2508.06530 (2025) - [i17]Wei Wang, Tianhao Ma, Ming-Kun Xie, Gang Niu, Masashi Sugiyama:
Rethinking Consistent Multi-Label Classification under Inexact Supervision. CoRR abs/2510.04091 (2025) - [i16]Zhiqiang Kou, Junyang Chen, Xin-Qiang Cai, Ming-Kun Xie, Biao Liu, Changwei Wang, Lei Feng, Yuheng Jia, Gang Niu, Masashi Sugiyama, Xin Geng:
Rethinking Toxicity Evaluation in Large Language Models: A Multi-Label Perspective. CoRR abs/2510.15007 (2025) - [i15]Pei Peng, Ming-Kun Xie, Hang Hao, Tong Jin, Sheng-Jun Huang:
Representation-Level Counterfactual Calibration for Debiased Zero-Shot Recognition. CoRR abs/2510.26466 (2025) - 2024
- [j6]Haochen Shi, Ming-Kun Xie, Shengjun Huang:
Robust AUC maximization for classification with pairwise confidence comparisons. Frontiers Comput. Sci. 18(4) (2024) - [j5]Feng Sun, Ming-Kun Xie, Sheng-Jun Huang:
A Deep Model for Partial Multi-label Image Classification with Curriculum-based Disambiguation. Mach. Intell. Res. 21(4): 801-814 (2024) - [j4]Quan Feng, Jia-Yu Yao, Ming-Kun Xie, Sheng-Jun Huang, Songcan Chen:
Sequential Cooperative Distillation for Imbalanced Multi-Task Learning. J. Comput. Sci. Technol. 39(5): 1094-1106 (2024) - [j3]Jia-Yao Chen, Shao-Yuan Li, Sheng-Jun Huang, Songcan Chen, Lei Wang, Ming-Kun Xie:
UNM: A Universal Approach for Noisy Multi-Label Learning. IEEE Trans. Knowl. Data Eng. 36(9): 4968-4980 (2024) - [c17]Wenhai Wan, Xinrui Wang, Ming-Kun Xie, Shao-Yuan Li, Sheng-Jun Huang, Songcan Chen:
Unlocking the Power of Open Set: A New Perspective for Open-Set Noisy Label Learning. AAAI 2024: 15438-15446 - [c16]Chen-Chen Zong, Ye-Wen Wang, Ming-Kun Xie, Sheng-Jun Huang:
Dirichlet-Based Prediction Calibration for Learning with Noisy Labels. AAAI 2024: 17254-17262 - [c15]Jiahao Xiao, Ming-Kun Xie, Heng-Bo Fan, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang:
Dual-Decoupling Learning and Metric-Adaptive Thresholding for Semi-supervised Multi-label Learning. ECCV (52) 2024: 437-454 - [c14]Ye-Wen Wang, Chen-Chen Zong, Ming-Kun Xie, Sheng-Jun Huang:
Dirichlet-Based Coarse-to-Fine Example Selection For Open-Set Annotation. ICME 2024: 1-6 - [c13]Ming-Kun Xie, Jiahao Xiao, Pei Peng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang:
Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training. ICML 2024: 54576-54589 - [c12]Hao-Zhe Liu, Ming-Kun Xie, Chen-Chen Zong, Sheng-Jun Huang:
Asymmetric Beta Loss for Evidence-Based Safe Semi-Supervised Multi-Label Learning. KDD 2024: 1909-1920 - [c11]Qin-Wen Luo, Ming-Kun Xie, Ye-Wen Wang, Sheng-Jun Huang:
Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL. NeurIPS 2024 - [i14]Chen-Chen Zong, Ye-Wen Wang, Ming-Kun Xie, Sheng-Jun Huang:
Dirichlet-Based Prediction Calibration for Learning with Noisy Labels. CoRR abs/2401.07062 (2024) - [i13]Ming-Kun Xie, Jiahao Xiao, Pei Peng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang:
Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training. CoRR abs/2404.06287 (2024) - [i12]Jiahao Xiao, Ming-Kun Xie, Heng-Bo Fan, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang:
Dual-Decoupling Learning and Metric-Adaptive Thresholding for Semi-Supervised Multi-Label Learning. CoRR abs/2407.18624 (2024) - [i11]Ye-Wen Wang, Chen-Chen Zong, Ming-Kun Xie, Sheng-Jun Huang:
Dirichlet-Based Coarse-to-Fine Example Selection For Open-Set Annotation. CoRR abs/2409.17607 (2024) - [i10]Heng-Bo Fan, Ming-Kun Xie, Jiahao Xiao, Sheng-Jun Huang:
Context-Based Semantic-Aware Alignment for Semi-Supervised Multi-Label Learning. CoRR abs/2412.18842 (2024) - [i9]Qin-Wen Luo, Ming-Kun Xie, Ye-Wen Wang, Sheng-Jun Huang:
Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL. CoRR abs/2412.18855 (2024) - 2023
- [j2]Ming-Kun Xie, Sheng-Jun Huang:
CCMN: A General Framework for Learning With Class-Conditional Multi-Label Noise. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 154-166 (2023) - [c10]Penghui Yang, Ming-Kun Xie, Chen-Chen Zong, Lei Feng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang:
Multi-Label Knowledge Distillation. ICCV 2023: 17225-17234 - [c9]Ming-Kun Xie, Jiahao Xiao, Hao-Zhe Liu, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang:
Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning. NeurIPS 2023 - [i8]Ming-Kun Xie, Jiahao Xiao, Hao-Zhe Liu, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang:
Class-Distribution-Aware Pseudo Labeling for Semi-Supervised Multi-Label Learning. CoRR abs/2305.02795 (2023) - [i7]Wenhai Wan, Xinrui Wang, Ming-Kun Xie, Shengjun Huang, Songcan Chen, Shaoyuan Li:
Unlocking the Power of Open Set : A New Perspective for Open-set Noisy Label Learning. CoRR abs/2305.04203 (2023) - [i6]Penghui Yang, Ming-Kun Xie, Chen-Chen Zong, Lei Feng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang:
Multi-Label Knowledge Distillation. CoRR abs/2308.06453 (2023) - 2022
- [j1]Ming-Kun Xie, Sheng-Jun Huang:
Partial Multi-Label Learning With Noisy Label Identification. IEEE Trans. Pattern Anal. Mach. Intell. 44(7): 3676-3687 (2022) - [c8]Ming-Kun Xie, Jiahao Xiao, Sheng-Jun Huang:
Label-Aware Global Consistency for Multi-Label Learning with Single Positive Labels. NeurIPS 2022 - [i5]Feng Sun, Ming-Kun Xie, Sheng-Jun Huang:
A Deep Model for Partial Multi-Label Image Classification with Curriculum Based Disambiguation. CoRR abs/2207.02410 (2022) - [i4]Bo-Shi Zou, Ming-Kun Xie, Sheng-Jun Huang:
Meta Objective Guided Disambiguation for Partial Label Learning. CoRR abs/2208.12459 (2022) - [i3]Chen-Chen Zong, Zheng-Tao Cao, Hong-Tao Guo, Yun Du, Ming-Kun Xie, Shao-Yuan Li, Sheng-Jun Huang:
Noise-Robust Bidirectional Learning with Dynamic Sample Reweighting. CoRR abs/2209.01334 (2022) - 2021
- [c7]Ming-Kun Xie, Feng Sun, Sheng-Jun Huang:
Partial Multi-Label Learning with Meta Disambiguation. KDD 2021: 1904-1912 - [c6]Ming-Kun Xie, Sheng-Jun Huang:
Multi-Label Learning with Pairwise Relevance Ordering. NeurIPS 2021: 23545-23556 - [i2]Ming-Kun Xie, Sheng-Jun Huang:
CCMN: A General Framework for Learning with Class-Conditional Multi-Label Noise. CoRR abs/2105.07338 (2021) - 2020
- [c5]Ming-Kun Xie, Sheng-Jun Huang:
Partial Multi-Label Learning with Noisy Label Identification. AAAI 2020: 6454-6461 - [c4]Ming-Kun Xie, Sheng-Jun Huang:
Semi-Supervised Partial Multi-Label Learning. ICDM 2020: 691-700
2010 – 2019
- 2019
- [c3]Ming-Kun Xie, Sheng-Jun Huang:
Learning Class-Conditional GANs with Active Sampling. KDD 2019: 998-1006 - 2018
- [c2]Ming-Kun Xie, Sheng-Jun Huang:
Partial Multi-Label Learning. AAAI 2018: 4302-4309 - [c1]Sheng-Jun Huang, Miao Xu, Ming-Kun Xie, Masashi Sugiyama, Gang Niu, Songcan Chen:
Active Feature Acquisition with Supervised Matrix Completion. KDD 2018: 1571-1579 - [i1]Sheng-Jun Huang, Miao Xu, Ming-Kun Xie, Masashi Sugiyama, Gang Niu, Songcan Chen:
Active Feature Acquisition with Supervised Matrix Completion. CoRR abs/1802.05380 (2018)
Coauthor Index
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last updated on 2026-02-28 00:41 CET by the dblp team
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