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Xie, Ming-Kun
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1

UNM: A Universal Approach for Noisy Multi-label Learning:

Chen, Jia-Yao ; Li, Shao-Yuan ; Huang, Sheng-Jun...
IEEE Transactions on Knowledge and Data Engineering.  , 2024
Link: https://doi.org/10.1109/..
 
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2

Multi-Label Knowledge Distillation:

, In: 2023 IEEE/CVF International Conference on Computer Vision (ICCV),
Yang, Penghui ; Xie, Ming-Kun ; Zong, Chen-Chen... - p. 17225-17234 , 2023
Link: https://doi.org/10.1109/..
 
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3

CCMN: A General Framework for Learning With Class-Condition..:

Xie, Ming-Kun ; Huang, Sheng-Jun
IEEE Transactions on Pattern Analysis and Machine Intelligence.  45 (2023)  1 - p. 154-166 , 2023
Link: https://doi.org/10.1109/..
 
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4

Partial Multi-Label Learning with Meta Disambiguation:

, In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining,
Xie, Ming-Kun ; Sun, Feng ; Huang, Sheng-Jun - p. 1904-1912 , 2021
Link: https://dl.acm.org/doi/1..
 
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5

Partial Multi-Label Learning with Noisy Label Identificatio:

Xie, Ming-Kun ; Huang, Sheng-Jun
IEEE Transactions on Pattern Analysis and Machine Intelligence.  , 2021
Link: https://doi.org/10.1109/..
 
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6

Semi-Supervised Partial Multi-label Learning:

, In: 2020 IEEE International Conference on Data Mining (ICDM),
Xie, Ming-Kun ; Huang, Sheng-Jun - p. 691-700 , 2020
Link: https://doi.org/10.1109/..
 
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7

Learning Class-Conditional GANs with Active Sampling:

, In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining,
Xie, Ming-Kun ; Huang, Sheng-Jun - p. 998-1006 , 2019
Link: https://dl.acm.org/doi/1..
 
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8

Active Feature Acquisition with Supervised Matrix Completio:

, In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining,
Huang, Sheng-Jun ; Xu, Miao ; Xie, Ming-Kun... - p. 1571-1579 , 2018
Link: https://dl.acm.org/doi/1..
 
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9

Dirichlet-Based Prediction Calibration for Learning with No..:

Zong, Chen-Chen ; Wang, Ye-Wen ; Xie, Ming-Kun.
http://arxiv.org/abs/2401.07062.  , 2024
Link: http://arxiv.org/abs/240..
 
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10

Multi-Label Knowledge Distillation:

Yang, Penghui ; Xie, Ming-Kun ; Zong, Chen-Chen...
http://arxiv.org/abs/2308.06453.  , 2023
Link: http://arxiv.org/abs/230..
 
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11

Class-Distribution-Aware Pseudo Labeling for Semi-Supervise..:

Xie, Ming-Kun ; Xiao, Jia-Hao ; Liu, Hao-Zhe...
http://arxiv.org/abs/2305.02795.  , 2023
Link: http://arxiv.org/abs/230..
 
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12

A Deep Model for Partial Multi-Label Image Classification w..:

Sun, Feng ; Xie, Ming-Kun ; Huang, Sheng-Jun
http://arxiv.org/abs/2207.02410.  , 2022
Link: http://arxiv.org/abs/220..
 
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13

Meta Objective Guided Disambiguation for Partial Label Lear..:

Zou, Bo-Shi ; Xie, Ming-Kun ; Huang, Sheng-Jun
http://arxiv.org/abs/2208.12459.  , 2022
Link: http://arxiv.org/abs/220..
 
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14

Noise-Robust Bidirectional Learning with Dynamic Sample Rew..:

Zong, Chen-Chen ; Cao, Zheng-Tao ; Guo, Hong-Tao...
http://arxiv.org/abs/2209.01334.  , 2022
Link: http://arxiv.org/abs/220..
 
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15

CCMN: A General Framework for Learning with Class-Condition..:

Xie, Ming-Kun ; Huang, Sheng-Jun
http://arxiv.org/abs/2105.07338.  , 2021
Link: http://arxiv.org/abs/210..
 
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