Preprints

1. Yi Gao, Miao Xu, Min-Ling Zhang. Complementary to Multiple Labels: A Correlation-Aware Correction Approach. arXiv: 2302.12987, 2023
2. Yawen Zhao, Mingzhe Zhang, Chenhao Zhang, Weitong Chen, Nan Ye, Miao Xu. A Boosting Algorithm for Positive-Unlabeled Learning. arXiv: 2205.09485, 2022.
3. Cheng-Yu Hsieh, Wei-I Lin, Miao Xu, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama. Active Refinement for Multi-Label Learning: A Pseudo-Label Approach. arXiv:2109.14676, 2021.
4. Miao Xu, Bingcong Li, Gang Niu, Bo Han, Masashi Sugiyama. Revisiting Sample Selection Approach to Positive-Unlabeled Learning: Turning Unlabeled Data into Positive rather than NegativearXiv:1901.10155, 2019
5. Miao Xu, Gang Niu, Bo Han, Ivor W. Tsang, Zhi-Hua Zhou, Masashi Sugiyama. Matrix Co-completion for Multi-label Classification with Missing Features and Labels. arXiv:1805.09156, 2018.

Conference

1. Yi Gao, Yong-Gang Luo, Ju-Cheng Yang, Miao Xu, Min-Ling Zhang. Unlearning From Weakly Supervised Learning. IJCAI 2024.
2. Shaofei Shen, Chenhao Zhang, Yawen Zhao, Alina Bialkowski, Weitong Chen, Miao Xu. Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models. ICLR 2024.
3. Tong Wang, Yuan Yao, Feng Xu, Miao Xu, Shengwei An, Ting Wang. Inspecting Prediction Confidence for Detecting Black-Box Backdoor Attacks. AAAI 2024.
4. Shaofei Shen, Chenhao Zhang, Yawen Zhao, Alina Bialkowski, Weitong Chen, Miao Xu. CaMU: Disentangling Causal Effects in Deep Model Unlearning. SDM 2024
5. Yixuan Qiu, Weitong Chen, Miao Xu. A Progressive Sampling Method for Dual-Node Imbalanced Learning with Restricted Data Access. ICDM 2023 (Long Paper).
6. Yi Gao, Miao Xu, Min-Ling Zhang. Unbiased risk estimator to multi-labeled complementary label learning. IJCAI 2023.
7. Shaofei Shen, Mingzhe Zhang, Weitong Chen, Alina Bialkowski, Miao Xu. Words Can be Confusing: Stereotype Bias Removal in Text Classification at the Word Level. PAKDD 2023.
8. Jonathan Wilton, Abigail M. Y. Koay, Ryan K. L. Ko, Miao Xu, Nan Ye. Positive-Unlabeled Learning using Random Forests via Recursive Greedy Risk Minimization. NeurIPS 2022
9. Ji Liu, Zenan Li, Yuan Yao, Feng Xu, Xiaoxing Ma, Miao Xu, Hanghang Tong. Fair Representation Learning: An Alternative to Mutual Information. KDD 2022: 1088-1097
10. Shaofei Shen, Weitong Chen, Miao Xu. What Leads to Arrhythmia: Active Causal Representation Learning of ECG Classification. AI 2022: 501-515
11. Mingzhe Zhang, Lin Yue, Miao Xu. ESTD: Empathy Style Transformer with Discriminative Mechanism. ADMA (2) 2022: 58-72
12. Yawen Zhao, Lin Yue, Miao Xu. A Boosting Algorithm for Training from Only Unlabeled Data. ADMA (2) 2022: 459-473
13. Shaofei Shen, Miao Xu, Lin Yue, Robert Boots, Weitong Chen. Death Comes But Why: An Interpretable Illness Severity Predictions in ICU. APWeb/WAIM (1) 2022: 60-75
14. Chenhao Zhang, Yanjun Zhang, Jeff Mao, Weitong Chen, Lin Yue, Guangdong Bai, Miao Xu. Towards Better Generalization for Neural Network-Based SAT Solvers. PAKDD (2) 2022: 199-210
15. Yanda Wang, Weitong Chen, Dechang Pi, Lin Yue, Miao Xu, Xue Li. Multi-hop Reading on Memory Neural Network with Selective Coverage for Medication Recommendation. CIKM 2021: 2020-2029
16. Yanda Wang, Weitong Chen, Dechang Pi, Lin Yue, Sen Wang, Miao Xu. Self-Supervised Adversarial Distribution Regularization for Medication Recommendation. IJCAI 2021: 3134-3140
17. Guangxin Su, Weitong Chen, Miao Xu. Positive-Unlabeled Learning from Imbalanced Data. IJCAI 2021: 2995-3001
18. Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama. Pointwise Binary Classification with Pairwise Confidence Comparisons. ICML 2021: 3252-3262
19. Khai Phan Tran, Weitong Chen, Miao Xu. Improving Traffic Load Prediction with Multi-modality - A Case Study of Brisbane. AI 2021: 254-266
20. Kun Han, Weitong Chen, Miao Xu. Investigating Active Positive-Unlabeled Learning with Deep Networks. AI 2021: 607-618
21. Yixuan Qiu, Weitong Chen, Lin Yue, Miao Xu, Baofeng Zhu. STCT: Spatial-Temporal Conv-Transformer Network for Cardiac Arrhythmias Recognition. ADMA 2021: 86-100
22. Long Chen, Yuan Yao, Feng Xu, Miao Xu, Hanghang Tong. Trading Personalization for Accuracy: Data Debugging in Collaborative Filtering. NeurIPS 2020
23. Lei Feng, Jiaqi Lv, Bo Han, Miao Xu, Gang Niu, Xin Geng, Bo An, Masashi Sugiyama. Provably Consistent Partial-Label Learning. NeurIPS 2020
24. Jiaqi Lv, Miao Xu, Lei Feng, Gang Niu, Xin Geng, Masashi Sugiyama. Progressive Identification of True Labels for Partial-Label Learning. ICML 2020: 6500-6510
25. Bo Han, Gang Niu, Xingrui Yu, Quanming Yao, Miao Xu, Ivor W. Tsang, Masashi Sugiyama. SIGUA: Forgetting May Make Learning with Noisy Labels More Robust. ICML 2020: 4006-4016
26. Takeshi Teshima, Miao Xu, Issei Sato, Masashi Sugiyama. Clipped Matrix Completion: A Remedy for Ceiling Effects. AAAI 2019: 5151-5158
27. Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor W. Tsang, Masashi Sugiyama. Co-teaching: Robust training of deep neural networks with extremely noisy labels. NeurIPS 2018: 8536-8546
28. 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
29. Miao Xu, Rong Jin, Zhi-Hua Zhou. CUR Algorithm for Partially Observed Matrices. ICML 2015: 1412-1421
30. Miao Xu, Zhi-Hua Zhou. Incomplete Label Distribution Learning. IJCAI 2017: 3175-3181
31. Miao Xu, Rong Jin, Zhi-Hua Zhou. Speedup Matrix Completion with Side Information: Application to Multi-Label Learning. NIPS 2013: 2301-2309
32. Miao Xu, Yu-Feng Li, Zhi-Hua Zhou. Multi-Label Learning with PRO Loss. AAAI 2013

Journal

1. Chenhao Zhang, Weitong Chen, Wei Emma Zhang, Miao Xu. Mitigating the Impact of Inaccurate Feedback in Dynamic Learning-to-Rank: A Study of Overlooked Interesting Items. ACM Transactions on Intelligent Systems and Technology, Accepted
2. Jiaqi Lv, Biao Liu, Lei Feng, Ning Xu, Miao Xu, Bo An, Gang Niu, Xin Geng, Masashi Sugiyama. On the Robustness of Average Losses for Partial-Label Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(5): 2569 - 2583 (2023)
3. Yixuan Qiu, Feng Lin, Weitong Chen, Miao Xu. Pre-training in Medical Data: A Survey. Machine Intelligence Research (2023)
4. Guanhua Ye, Hongzhi Yin, Tong Chen, Miao Xu, Quoc Viet Hung Nguyen, Jiangning Song. Personalized On-Device E-Health Analytics With Decentralized Block Coordinate Descent. IEEE J. Biomed. Health Informatics 26(6): 2778-2786 (2022)
5. Miao Xu, Lan-Zhe Guo. Learning from group supervision: the impact of supervision deficiency on multi-label learning. Science China Informationis. 64(3) (2021)
6. Miao Xu, Yu-Feng Li, Zhi-Hua Zhou. Robust Multi-Label Learning with PRO Loss. IEEE Trans. Knowl. Data Eng. 32(8): 1610-1624 (2020)
7. Miao Xu, Zhi-Hua Zhou. Kernel method for matrix completion with side information and its application in multi-label learning. Science China Informationis. 48(1): 47-59, (2017)