Ming-Kun Xie

According to our database, Ming-Kun Xie authored at least 23 papers between 2018 and 2024.

Collaborative distances:

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

2024

UNM: A Universal Approach for Noisy Multi-Label Learning.

Jia-Yao Chen, Shao-Yuan Li, Sheng-Jun Huang, Songcan Chen, Lei Wang, Ming-Kun Xie

IEEE Trans. Knowl. Data Eng., September, 2024

A Deep Model for Partial Multi-label Image Classification with Curriculum-based Disambiguation.

Feng Sun, Ming-Kun Xie, Sheng-Jun Huang

Mach. Intell. Res., August, 2024

Robust AUC maximization for classification with pairwise confidence comparisons.

Haochen Shi, Ming-Kun Xie, Shengjun Huang

Frontiers Comput. Sci., August, 2024

Dual-Decoupling Learning and Metric-Adaptive Thresholding for Semi-Supervised Multi-Label Learning.

Jiahao Xiao, Ming-Kun Xie, Heng-Bo Fan, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang

CoRR, 2024

Asymmetric Beta Loss for Evidence-Based Safe Semi-Supervised Multi-Label Learning.

Hao-Zhe Liu, Ming-Kun Xie, Chen-Chen Zong, Sheng-Jun Huang

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training.

Ming-Kun Xie, Jiahao Xiao, Pei Peng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Dirichlet-Based Coarse-to-Fine Example Selection For Open-Set Annotation.

Ye-Wen Wang, Chen-Chen Zong, Ming-Kun Xie, Sheng-Jun Huang

Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

Dirichlet-Based Prediction Calibration for Learning with Noisy Labels.

Chen-Chen Zong, Ye-Wen Wang, Ming-Kun Xie, Sheng-Jun Huang

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

Unlocking the Power of Open Set: A New Perspective for Open-Set Noisy Label Learning.

Wenhai Wan, Xinrui Wang, Ming-Kun Xie, Shao-Yuan Li, Sheng-Jun Huang, Songcan Chen

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

2023

CCMN: A General Framework for Learning With Class-Conditional Multi-Label Noise.

Ming-Kun Xie, Sheng-Jun Huang

IEEE Trans. Pattern Anal. Mach. Intell., 2023

Unlocking the Power of Open Set : A New Perspective for Open-set Noisy Label Learning.

Wenhai Wan, Xinrui Wang, Ming-Kun Xie, Shengjun Huang, Songcan Chen, Shaoyuan Li

CoRR, 2023

Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning.

Ming-Kun Xie, Jiahao Xiao, Hao-Zhe Liu, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multi-Label Knowledge Distillation.

Penghui Yang, Ming-Kun Xie, Chen-Chen Zong, Lei Feng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Partial Multi-Label Learning With Noisy Label Identification.

Ming-Kun Xie, Sheng-Jun Huang

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Noise-Robust Bidirectional Learning with Dynamic Sample Reweighting.

Chen-Chen Zong, Zheng-Tao Cao, Hong-Tao Guo, Yun Du, Ming-Kun Xie, Shao-Yuan Li, Sheng-Jun Huang

CoRR, 2022

Meta Objective Guided Disambiguation for Partial Label Learning.

Bo-Shi Zou, Ming-Kun Xie, Sheng-Jun Huang

CoRR, 2022

Label-Aware Global Consistency for Multi-Label Learning with Single Positive Labels.

Ming-Kun Xie, Jiahao Xiao, Sheng-Jun Huang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Multi-Label Learning with Pairwise Relevance Ordering.

Ming-Kun Xie, Sheng-Jun Huang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Partial Multi-Label Learning with Meta Disambiguation.

Ming-Kun Xie, Feng Sun, Sheng-Jun Huang

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020

Semi-Supervised Partial Multi-Label Learning.

Ming-Kun Xie, Sheng-Jun Huang

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2019

Learning Class-Conditional GANs with Active Sampling.

Ming-Kun Xie, Sheng-Jun Huang

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2018

Active Feature Acquisition with Supervised Matrix Completion.

Sheng-Jun Huang, Miao Xu, Ming-Kun Xie, Masashi Sugiyama, Gang Niu, Songcan Chen

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Partial Multi-Label Learning.

Ming-Kun Xie, Sheng-Jun Huang

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018