Multi-Label Learning with PRO Loss. - Miao Xu 001; Yufeng Li 008; Zhi-Hua Zhou (AAAI, 2013)

Speedup Matrix Completion with Side Information: Application to Multi-Label Learning. - Miao Xu 001; Rong Jin 001; Zhi-Hua Zhou (NIPS, 2013)

CUR Algorithm for Partially Observed Matrices. - Miao Xu 001; Rong Jin 001; Zhi-Hua Zhou (ICML, 2015)

Incomplete Label Distribution Learning. - Miao Xu 001; Zhi-Hua Zhou (IJCAI, 2017)

Active Feature Acquisition with Supervised Matrix Completion. - Sheng-Jun Huang; Miao Xu 001; Ming-Kun Xie; Masashi Sugiyama; Gang Niu 001; Songcan Chen (KDD, 2018)

Co-teaching: Robust training of deep neural networks with extremely noisy labels. - Bo Han 003; Quanming Yao; Xingrui Yu; Gang Niu 001; Miao Xu 001; Weihua Hu; Ivor W. Tsang; Masashi Sugiyama (NeurIPS, 2018)

Co-sampling: Training Robust Networks for Extremely Noisy Supervision. - Bo Han 003; Quanming Yao; Xingrui Yu; Gang Niu 001; Miao Xu 001; Weihua Hu; Ivor W. Tsang; Masashi Sugiyama (CoRR, 2018)

Matrix Co-completion for Multi-label Classification with Missing Features and Labels. - Miao Xu 001; Gang Niu 001; Bo Han 003; Ivor W. Tsang; Zhi-Hua Zhou; Masashi Sugiyama (CoRR, 2018)

Pumpout: A Meta Approach for Robustly Training Deep Neural Networks with Noisy Labels. - Bo Han 003; Gang Niu 001; Jiangchao Yao; Xingrui Yu; Miao Xu 001; Ivor W. Tsang; Masashi Sugiyama (CoRR, 2018)

Clipped Matrix Completion: A Remedy for Ceiling Effects. - Takeshi Teshima; Miao Xu 001; Issei Sato; Masashi Sugiyama (AAAI, 2019)

Revisiting Sample Selection Approach to Positive-Unlabeled Learning: Turning Unlabeled Data into Positive rather than Negative. - Miao Xu 001; Bingcong Li; Gang Niu 001; Bo Han 003; Masashi Sugiyama (CoRR, 2019)

SIGUA: Forgetting May Make Learning with Noisy Labels More Robust. - Bo Han 003; Gang Niu 001; Xingrui Yu; Quanming Yao; Miao Xu 001; Ivor W. Tsang; Masashi Sugiyama (ICML, 2020)

Progressive Identification of True Labels for Partial-Label Learning. - Jiaqi Lv; Miao Xu 001; Lei Feng 006; Gang Niu 001; Xin Geng 001; Masashi Sugiyama (ICML, 2020)

Trading Personalization for Accuracy: Data Debugging in Collaborative Filtering. - Long Chen; Yuan Yao 001; Feng Xu 007; Miao Xu 001; Hanghang Tong (NeurIPS, 2020)

Provably Consistent Partial-Label Learning. - Lei Feng 006; Jiaqi Lv; Bo Han 003; Miao Xu 001; Gang Niu 001; Xin Geng 001; Bo An 001; Masashi Sugiyama (NeurIPS, 2020)

Robust Multi-Label Learning with PRO Loss. - Miao Xu 001; Yufeng Li 008; Zhi-Hua Zhou (IEEE Trans. Knowl. Data Eng., 2020)

STCT: Spatial-Temporal Conv-Transformer Network for Cardiac Arrhythmias Recognition. - Yixuan Qiu; Weitong Chen 001; Lin Yue; Miao Xu 001; Baofeng Zhu (ADMA, 2021)

Multi-hop Reading on Memory Neural Network with Selective Coverage for Medication Recommendation. - Yanda Wang; Weitong Chen 001; Dechang Pi; Lin Yue; Miao Xu 001; Xue Li 001 (CIKM, 2021)

Pointwise Binary Classification with Pairwise Confidence Comparisons. - Lei Feng 006; Senlin Shu; Nan Lu; Bo Han 003; Miao Xu 001; Gang Niu 001; Bo An 001; Masashi Sugiyama (ICML, 2021)

Positive-Unlabeled Learning from Imbalanced Data. - Guangxin Su; Weitong Chen 001; Miao Xu 001 (IJCAI, 2021)

Self-Supervised Adversarial Distribution Regularization for Medication Recommendation. - Yanda Wang; Weitong Chen 001; Dechang Pi; Lin Yue; Sen Wang 001; Miao Xu 001 (IJCAI, 2021)

Learning from group supervision: the impact of supervision deficiency on multi-label learning. - Miao Xu 001; Lan-Zhe Guo (Sci. China Inf. Sci., 2021)

On the Robustness of Average Losses for Partial-Label Learning. - Jiaqi Lv; Lei Feng 006; Miao Xu 001; Bo An 001; Gang Niu 001; Xin Geng 001; Masashi Sugiyama (CoRR, 2021)

Active Refinement for Multi-Label Learning: A Pseudo-Label Approach. - Cheng-Yu Hsieh; Wei-I Lin; Miao Xu 001; Gang Niu 001; Hsuan-Tien Lin; Masashi Sugiyama (CoRR, 2021)

ESTD: Empathy Style Transformer with Discriminative Mechanism. - Mingzhe Zhang; Lin Yue; Miao Xu 001 (ADMA (2), 2022)

A Boosting Algorithm for Training from Only Unlabeled Data. - Yawen Zhao 002; Lin Yue; Miao Xu 001 (ADMA (2), 2022)

Death Comes But Why: An Interpretable Illness Severity Predictions in ICU. - Shaofei Shen 001; Miao Xu 001; Lin Yue; Robert Boots; Weitong Chen 001 (APWeb/WAIM (1), 2022)

Investigating Active Positive-Unlabeled Learning with Deep Networks. - Kun Han; Weitong Chen 001; Miao Xu 001 (AI, 2022)

What Leads to Arrhythmia: Active Causal Representation Learning of ECG Classification. - Shaofei Shen 001; Weitong Chen 001; Miao Xu 001 (AI, 2022)

Improving Traffic Load Prediction with Multi-modality - A Case Study of Brisbane. - Khai Phan Tran; Weitong Chen 001; Miao Xu 001 (AI, 2022)

Fair Representation Learning: An Alternative to Mutual Information. - Ji Liu; Zenan Li; Yuan Yao 001; Feng Xu 007; Xiaoxing Ma; Miao Xu 001; Hanghang Tong (KDD, 2022)

Positive-Unlabeled Learning using Random Forests via Recursive Greedy Risk Minimization. - Jonathan Wilton; Abigail M. Y. Koay; Ryan K. L. Ko; Miao Xu 001; Nan Ye (NeurIPS, 2022)

Towards Better Generalization for Neural Network-Based SAT Solvers. - Chenhao Zhang 004; Yanjun Zhang; Jeff Mao; Weitong Chen 001; Lin Yue; Guangdong Bai; Miao Xu 001 (PAKDD (2), 2022)

A Boosting Algorithm for Positive-Unlabeled Learning. - Yawen Zhao 002; Mingzhe Zhang; Chenhao Zhang 004; Tony Chen 001; Nan Ye; Miao Xu 001 (CoRR, 2022)

Confidence Matters: Inspecting Backdoors in Deep Neural Networks via Distribution Transfer. - Tong Wang; Yuan Yao 001; Feng Xu 007; Miao Xu 001; Shengwei An; Ting Wang 006 (CoRR, 2022)

Personalized On-Device E-Health Analytics With Decentralized Block Coordinate Descent. - Guanhua Ye; Hongzhi Yin; Tong Chen 005; Miao Xu 001; Quoc Viet Hung Nguyen; Jiangning Song (IEEE J. Biomed. Health Informatics, 2022)

A Progressive Sampling Method for Dual-Node Imbalanced Learning with Restricted Data Access. - Yixuan Qiu; Weitong Chen 001; Miao Xu 001 (ICDM, 2023)

Unbiased Risk Estimator to Multi-Labeled Complementary Label Learning. - Yi Gao 003; Miao Xu 001; Min-Ling Zhang (IJCAI, 2023)

Words Can Be Confusing: Stereotype Bias Removal in Text Classification at the Word Level. - Shaofei Shen 001; Mingzhe Zhang; Weitong Chen 001; Alina Bialkowski; Miao Xu 001 (PAKDD (4), 2023)

Pre-training in Medical Data: A Survey. - Yixuan Qiu; Feng Lin; Weitong Chen 001; Miao Xu 001 (Mach. Intell. Res., 2023)

Inspecting Prediction Confidence for Detecting Black-Box Backdoor Attacks. - Tong Wang; Yuan Yao 001; Feng Xu 007; Miao Xu 001; Shengwei An; Ting Wang 006 (AAAI, 2024)

Countering Relearning with Perception Revising Unlearning. - Chenhao Zhang 004; Weitong Chen 001; Wei Emma Zhang; Miao Xu 001 (ACML, 2024)

Mining Irregular Time Series Data with Noisy Labels: A Risk Estimation Approach. - Kun Han; Abigail M. Y. Koay; Ryan K. L. Ko; Weitong Chen 001; Miao Xu 001 (ADC, 2024)

Irregularity-Informed Time Series Analysis: Adaptive Modelling of Spatial and Temporal Dynamics. - Liangwei Nathan Zheng; Zhengyang Li; Chang George Dong; Wei Emma Zhang; Lin Yue; Miao Xu 001; Olaf Maennel; Weitong Chen 001 (CIKM, 2024)

Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models. - Shaofei Shen 001; Chenhao Zhang 004; Yawen Zhao 002; Alina Bialkowski; Weitong Chen 001; Miao Xu 001 (ICLR, 2024)

Unlearning from Weakly Supervised Learning. - Yi Tang; Yi Gao 003; Yonggang Luo; Jucheng Yang; Miao Xu 001; Min-Ling Zhang (IJCAI, 2024)

Machine Unlearning: Challenges in Data Quality and Access. - Miao Xu 001 (IJCAI, 2024)

Emotionally Guided Symbolic Music Generation Using Diffusion Models: The AGE-DM Approach. - Mingzhe Zhang; Laura J. Ferris; Lin Yue; Miao Xu 001 (MMAsia, 2024)

What Makes Partial-Label Learning Algorithms Effective? - Jiaqi Lv; Yangfan Liu; Shiyu Xia; Ning Xu 009; Miao Xu 001; Gang Niu 001; Min-Ling Zhang; Masashi Sugiyama; Xin Geng 001 (NeurIPS, 2024)

CaMU: Disentangling Causal Effects in Deep Model Unlearning. - Shaofei Shen 001; Chenhao Zhang 004; Alina Bialkowski; Weitong Chen 001; Miao Xu 001 (SDM, 2024)

GENIU: A Restricted Data Access Unlearning for Imbalanced Data. - Chenhao Zhang 004; Shaofei Shen 001; Yawen Zhao 002; Weitong Tony Chen; Miao Xu 001 (CoRR, 2024)

Revisited Large Language Model for Time Series Analysis through Modality Alignment. - Liangwei Nathan Zheng; Chang George Dong; Wei Emma Zhang; Lin Yue; Miao Xu 001; Olaf Maennel; Weitong Chen 001 (CoRR, 2024)

On the Robustness of Average Losses for Partial-Label Learning. - Jiaqi Lv; Biao Liu; Lei Feng 006; Ning Xu 009; Miao Xu 001; Bo An 001; Gang Niu 001; Xin Geng 001; Masashi Sugiyama (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Complementary to Multiple Labels: A Correlation-Aware Correction Approach. - Yi Gao 003; Miao Xu 001; Min-Ling Zhang (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Toward Efficient Data-Free Unlearning. - Chenhao Zhang 004; Shaofei Shen 001; Weitong Chen 001; Miao Xu 001 (AAAI, 2025)

Cross-View Isolated Sign Language Recognition Challenge: Design, Results and Future Research. - Xin Shen; Heming Du; Miao Xu 001; Miaomiao Liu 001; Xin Yu 002 (WWW (Companion Volume), 2025)

Free-Knots Kolmogorov-Arnold Network: On the Analysis of Spline Knots and Advancing Stability. - Liangwewi Nathan Zheng; Wei Emma Zhang; Lin Yue; Miao Xu 001; Olaf Maennel; Weitong Chen 001 (CoRR, 2025)

A boosting framework for positive-unlabeled learning. - Yawen Zhao 002; Mingzhe Zhang; Chenhao Zhang 004; Weitong Chen 001; Nan Ye; Miao Xu 001 (Stat. Comput., 2025)

Mitigating the Impact of Inaccurate Feedback in Dynamic Learning-to-Rank: A Study of Overlooked Interesting Items. - Chenhao Zhang 004; Weitong Chen 001; Wei Zhang 098; Miao Xu 001 (ACM Trans. Intell. Syst. Technol., 2025)

PostHoc FREE Calibrating on Kolmogorov Arnold Networks. - Wenhao Liang; Wei Emma Zhang; Lin Yue; Miao Xu 001; Olaf Maennel; Weitong Chen 001 (CoRR, 2025)

We Care Each Pixel: Calibrating on Medical Segmentation Model. - Wenhao Liang; Wei Zhang 098; Yue Lin; Miao Xu 001; Olaf Maennel; Weitong Chen 001 (CoRR, 2025)

Rethinking Gating Mechanism in Sparse MoE: Handling Arbitrary Modality Inputs with Confidence-Guided Gate. - Liangwei Nathan Zheng; Wei Emma Zhang; Mingyu Guo; Miao Xu 001; Olaf Maennel; Weitong Chen 001 (CoRR, 2025)

Machine Unlearning for Streaming Forgetting. - Shaofei Shen 001; Chenhao Zhang 004; Yawen Zhao 002; Alina Bialkowski; Weitong Chen 001; Miao Xu 001 (CoRR, 2025)

Calibration Attention: Instance-wise Temperature Scaling for Vision Transformers. - Wenhao Liang; Wei Emma Zhang; Lin Yue; Miao Xu 001; Olaf Maennel; Weitong Chen 001 (CoRR, 2025)

Adapting to the stream: an instance-attention GNN method for irregular multivariate time series data. - Kun Han; Abigail M. Y. Koay; Ryan K. L. Ko; Weitong Chen 001; Miao Xu 001 (Frontiers Comput. Sci., 2025)

Multi-Label Learning With Multiple Complementary Labels. - Yi Gao 003; Jing-Yi Zhu; Miao Xu 001; Min-Ling Zhang (IEEE Trans. Pattern Anal. Mach. Intell., 2025)