Miao Xu - RankMe

88 papers A* 24A 7C 2Misc 4Journal 42Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Data Augmentation With Regularization for Multi-Labeled Complementary Label Learning. IEEE Trans. Pattern Anal. Mach. Intell. Yi Gao, Yuan-Yuan Meng, Miao Xu, Min-Ling Zhang
2026	A*	`conf`	Lifting Manifolds to Mitigate Pseudo-Alignment in LLM4TS. WWW Liangwei Nathan Zheng, Wenhao Liang, Wei Emma Zhang, Miao Xu, Olaf Maennel, Weitong Chen
2026	J	`jnl`	Test-Time Attention Purification for Backdoored Large Vision Language Models. CoRR Zhifang Zhang, Bojun Yang, Shuo He, Weitong Chen, Wei Emma Zhang, Olaf Maennel, Lei Feng, Miao Xu
2025	J	`jnl`	A boosting framework for positive-unlabeled learning. Stat. Comput. Yawen Zhao, Mingzhe Zhang, Chenhao Zhang, Weitong Chen, Nan Ye, Miao Xu
2025	J	`jnl`	Adapting to the stream: an instance-attention GNN method for irregular multivariate time series data. Frontiers Comput. Sci. Kun Han, Abigail M. Y. Koay, Ryan K. L. Ko, Weitong Chen, Miao Xu
2025	A	`conf`	Adaptive Spline Networks in the Kolmogorov-Arnold Framework: Knot Analysis and Stability Enhancement. CIKM Liangwei Nathan Zheng, Wei Emma Zhang, Lin Yue, Miao Xu, Olaf Maennel, Weitong Chen
2025	A	`conf`	Calibrating on Kolmogorov-Arnold Network. CIKM Wenhao Liang, Wei Emma Zhang, Lin Yue, Miao Xu, Olaf Maennel, Weitong Chen
2025	A	`conf`	Calibrating on Medical Segmentation Model through Signed Distance. CIKM Wenhao Liang, Wei Emma Zhang, Lin Yue, Miao Xu, Olaf Maennel, Weitong Chen
2025	J	`jnl`	Calibration Attention: Instance-wise Temperature Scaling for Vision Transformers. CoRR Wenhao Liang, Wei Emma Zhang, Lin Yue, Miao Xu, Olaf Maennel, Weitong Chen
2025	—	`conf`	Cross-View Isolated Sign Language Recognition Challenge: Design, Results and Future Research. WWW (Companion Volume) Xin Shen, Heming Du, Miao Xu, Miaomiao Liu, Xin Yu
2025	J	`jnl`	Free-Knots Kolmogorov-Arnold Network: On the Analysis of Spline Knots and Advancing Stability. CoRR Liangwewi Nathan Zheng, Wei Emma Zhang, Lin Yue, Miao Xu, Olaf Maennel, Weitong Chen
2025	J	`jnl`	Lifting Manifolds to Mitigate Pseudo-Alignment in LLM4TS. CoRR Liangwei Nathan Zheng, Wenhao Liang, Wei Emma Zhang, Miao Xu, Olaf Maennel, Weitong Chen
2025	A	`conf`	Machine Unlearning for Streaming Forgetting. ECAI Shaofei Shen, Chenhao Zhang, Yawen Zhao, Alina Bialkowski, Weitong Chen, Miao Xu
2025	J	`jnl`	Machine Unlearning for Streaming Forgetting. CoRR Shaofei Shen, Chenhao Zhang, Yawen Zhao, Alina Bialkowski, Weitong Chen, Miao Xu
2025	J	`jnl`	Mitigating the Impact of Inaccurate Feedback in Dynamic Learning-to-Rank: A Study of Overlooked Interesting Items. ACM Trans. Intell. Syst. Technol. Chenhao Zhang, Weitong Chen, Wei Zhang, Miao Xu
2025	J	`jnl`	Multi-Label Learning With Multiple Complementary Labels. IEEE Trans. Pattern Anal. Mach. Intell. Yi Gao, Jing-Yi Zhu, Miao Xu, Min-Ling Zhang
2025	J	`jnl`	PostHoc FREE Calibrating on Kolmogorov Arnold Networks. CoRR Wenhao Liang, Wei Emma Zhang, Lin Yue, Miao Xu, Olaf Maennel, Weitong Chen
2025	J	`jnl`	Rethinking Gating Mechanism in Sparse MoE: Handling Arbitrary Modality Inputs with Confidence-Guided Gate. CoRR Liangwei Nathan Zheng, Wei Emma Zhang, Mingyu Guo, Miao Xu, Olaf Maennel, Weitong Chen
2025	A*	`conf`	Toward Efficient Data-Free Unlearning. AAAI Chenhao Zhang, Shaofei Shen, Weitong Chen, Miao Xu
2025	—	`conf`	Understanding Why Large Language Models Can Be Ineffective in Time Series Analysis: The Impact of Modality Alignment. KDD (2) Liangwei Nathan Zheng, Chang George Dong, Wei Emma Zhang, Lin Yue, Miao Xu, Olaf Maennel, Weitong Chen
2025	J	`jnl`	We Care Each Pixel: Calibrating on Medical Segmentation Model. CoRR Wenhao Liang, Wei Zhang, Yue Lin, Miao Xu, Olaf Maennel, Weitong Chen
2024	A	`conf`	CaMU: Disentangling Causal Effects in Deep Model Unlearning. SDM Shaofei Shen, Chenhao Zhang, Alina Bialkowski, Weitong Chen, Miao Xu
2024	J	`jnl`	CaMU: Disentangling Causal Effects in Deep Model Unlearning. CoRR Shaofei Shen, Chenhao Zhang, Alina Bialkowski, Weitong Chen, Miao Xu
2024	J	`jnl`	Complementary to Multiple Labels: A Correlation-Aware Correction Approach. IEEE Trans. Pattern Anal. Mach. Intell. Yi Gao, Miao Xu, Min-Ling Zhang
2024	C	`conf`	Countering Relearning with Perception Revising Unlearning. ACML Chenhao Zhang, Weitong Chen, Wei Emma Zhang, Miao Xu
2024	—	`conf`	Emotionally Guided Symbolic Music Generation Using Diffusion Models: The AGE-DM Approach. MMAsia Mingzhe Zhang, Laura J. Ferris, Lin Yue, Miao Xu
2024	J	`jnl`	GENIU: A Restricted Data Access Unlearning for Imbalanced Data. CoRR Chenhao Zhang, Shaofei Shen, Yawen Zhao, Weitong Tony Chen, Miao Xu
2024	A*	`conf`	Inspecting Prediction Confidence for Detecting Black-Box Backdoor Attacks. AAAI Tong Wang, Yuan Yao, Feng Xu, Miao Xu, Shengwei An, Ting Wang
2024	A	`conf`	Irregularity-Informed Time Series Analysis: Adaptive Modelling of Spatial and Temporal Dynamics. CIKM Liangwei Nathan Zheng, Zhengyang Li, Chang George Dong, Wei Emma Zhang, Lin Yue, Miao Xu, Olaf Maennel, Weitong Chen
2024	J	`jnl`	Irregularity-Informed Time Series Analysis: Adaptive Modelling of Spatial and Temporal Dynamics. CoRR Liangwei Nathan Zheng, Zhengyang Li, Chang George Dong, Wei Emma Zhang, Lin Yue, Miao Xu, Olaf Maennel, Weitong Chen
2024	A*	`conf`	Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models. ICLR Shaofei Shen, Chenhao Zhang, Yawen Zhao, Alina Bialkowski, Weitong Chen, Miao Xu
2024	J	`jnl`	Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models. CoRR Shaofei Shen, Chenhao Zhang, Yawen Zhao, Alina Bialkowski, Weitong Chen, Miao Xu
2024	A*	`conf`	Machine Unlearning: Challenges in Data Quality and Access. IJCAI Miao Xu
2024	Misc	`conf`	Mining Irregular Time Series Data with Noisy Labels: A Risk Estimation Approach. ADC Kun Han, Abigail M. Y. Koay, Ryan K. L. Ko, Weitong Chen, Miao Xu
2024	J	`jnl`	On the Robustness of Average Losses for Partial-Label Learning. IEEE Trans. Pattern Anal. Mach. Intell. Jiaqi Lv, Biao Liu, Lei Feng, Ning Xu, Miao Xu, Bo An, Gang Niu, Xin Geng, Masashi Sugiyama
2024	J	`jnl`	Revisited Large Language Model for Time Series Analysis through Modality Alignment. CoRR Liangwei Nathan Zheng, Chang George Dong, Wei Emma Zhang, Lin Yue, Miao Xu, Olaf Maennel, Weitong Chen
2024	J	`jnl`	Toward Efficient Data-Free Unlearning. CoRR Chenhao Zhang, Shaofei Shen, Weitong Chen, Miao Xu
2024	A*	`conf`	Unlearning from Weakly Supervised Learning. IJCAI Yi Tang, Yi Gao, Yonggang Luo, Jucheng Yang, Miao Xu, Min-Ling Zhang
2024	A*	`conf`	What Makes Partial-Label Learning Algorithms Effective? NeurIPS Jiaqi Lv, Yangfan Liu, Shiyu Xia, Ning Xu, Miao Xu, Gang Niu, Min-Ling Zhang, Masashi Sugiyama, Xin Geng
2023	A*	`conf`	A Progressive Sampling Method for Dual-Node Imbalanced Learning with Restricted Data Access. ICDM Yixuan Qiu, Weitong Chen, Miao Xu
2023	J	`jnl`	Complementary to Multiple Labels: A Correlation-Aware Correction Approach. CoRR Yi Gao, Miao Xu, Min-Ling Zhang
2023	J	`jnl`	Pre-training in Medical Data: A Survey. Mach. Intell. Res. Yixuan Qiu, Feng Lin, Weitong Chen, Miao Xu
2023	A*	`conf`	Unbiased Risk Estimator to Multi-Labeled Complementary Label Learning. IJCAI Yi Gao, Miao Xu, Min-Ling Zhang
2023	—	`conf`	Words Can Be Confusing: Stereotype Bias Removal in Text Classification at the Word Level. PAKDD (4) Shaofei Shen, Mingzhe Zhang, Weitong Chen, Alina Bialkowski, Miao Xu
2022	J	`jnl`	A Boosting Algorithm for Positive-Unlabeled Learning. CoRR Yawen Zhao, Mingzhe Zhang, Chenhao Zhang, Tony Chen, Nan Ye, Miao Xu
2022	—	`conf`	A Boosting Algorithm for Training from Only Unlabeled Data. ADMA (2) Yawen Zhao, Lin Yue, Miao Xu
2022	J	`jnl`	Confidence Matters: Inspecting Backdoors in Deep Neural Networks via Distribution Transfer. CoRR Tong Wang, Yuan Yao, Feng Xu, Miao Xu, Shengwei An, Ting Wang
2022	—	`conf`	Death Comes But Why: An Interpretable Illness Severity Predictions in ICU. APWeb/WAIM (1) Shaofei Shen, Miao Xu, Lin Yue, Robert Boots, Weitong Chen
2022	—	`conf`	ESTD: Empathy Style Transformer with Discriminative Mechanism. ADMA (2) Mingzhe Zhang, Lin Yue, Miao Xu
2022	A*	`conf`	Fair Representation Learning: An Alternative to Mutual Information. KDD Ji Liu, Zenan Li, Yuan Yao, Feng Xu, Xiaoxing Ma, Miao Xu, Hanghang Tong
2022	Misc	`conf`	Improving Traffic Load Prediction with Multi-modality - A Case Study of Brisbane. AI Khai Phan Tran, Weitong Chen, Miao Xu
2022	Misc	`conf`	Investigating Active Positive-Unlabeled Learning with Deep Networks. AI Kun Han, Weitong Chen, Miao Xu
2022	J	`jnl`	Personalized On-Device E-Health Analytics With Decentralized Block Coordinate Descent. IEEE J. Biomed. Health Informatics Guanhua Ye, Hongzhi Yin, Tong Chen, Miao Xu, Quoc Viet Hung Nguyen, Jiangning Song
2022	A*	`conf`	Positive-Unlabeled Learning using Random Forests via Recursive Greedy Risk Minimization. NeurIPS Jonathan Wilton, Abigail M. Y. Koay, Ryan K. L. Ko, Miao Xu, Nan Ye
2022	J	`jnl`	Positive-Unlabeled Learning using Random Forests via Recursive Greedy Risk Minimization. CoRR Jonathan Wilton, Abigail M. Y. Koay, Ryan K. L. Ko, Miao Xu, Nan Ye
2022	—	`conf`	Towards Better Generalization for Neural Network-Based SAT Solvers. PAKDD (2) Chenhao Zhang, Yanjun Zhang, Jeff Mao, Weitong Chen, Lin Yue, Guangdong Bai, Miao Xu
2022	Misc	`conf`	What Leads to Arrhythmia: Active Causal Representation Learning of ECG Classification. AI Shaofei Shen, Weitong Chen, Miao Xu
2021	J	`jnl`	Active Refinement for Multi-Label Learning: A Pseudo-Label Approach. CoRR Cheng-Yu Hsieh, Wei-I Lin, Miao Xu, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama
2021	J	`jnl`	Learning from group supervision: the impact of supervision deficiency on multi-label learning. Sci. China Inf. Sci. Miao Xu, Lan-Zhe Guo
2021	A	`conf`	Multi-hop Reading on Memory Neural Network with Selective Coverage for Medication Recommendation. CIKM Yanda Wang, Weitong Chen, Dechang Pi, Lin Yue, Miao Xu, Xue Li
2021	J	`jnl`	On the Robustness of Average Losses for Partial-Label Learning. CoRR Jiaqi Lv, Lei Feng, Miao Xu, Bo An, Gang Niu, Xin Geng, Masashi Sugiyama
2021	J	`jnl`	Personalized On-Device E-health Analytics with Decentralized Block Coordinate Descent. CoRR Guanhua Ye, Hongzhi Yin, Tong Chen, Miao Xu, Quoc Viet Hung Nguyen, Jiangning Song
2021	A*	`conf`	Pointwise Binary Classification with Pairwise Confidence Comparisons. ICML Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama
2021	A*	`conf`	Positive-Unlabeled Learning from Imbalanced Data. IJCAI Guangxin Su, Weitong Chen, Miao Xu
2021	C	`conf`	STCT: Spatial-Temporal Conv-Transformer Network for Cardiac Arrhythmias Recognition. ADMA Yixuan Qiu, Weitong Chen, Lin Yue, Miao Xu, Baofeng Zhu
2021	A*	`conf`	Self-Supervised Adversarial Distribution Regularization for Medication Recommendation. IJCAI Yanda Wang, Weitong Chen, Dechang Pi, Lin Yue, Sen Wang, Miao Xu
2020	J	`jnl`	Pointwise Binary Classification with Pairwise Confidence Comparisons. CoRR Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama
2020	A*	`conf`	Progressive Identification of True Labels for Partial-Label Learning. ICML Jiaqi Lv, Miao Xu, Lei Feng, Gang Niu, Xin Geng, Masashi Sugiyama
2020	J	`jnl`	Progressive Identification of True Labels for Partial-Label Learning. CoRR Jiaqi Lv, Miao Xu, Lei Feng, Gang Niu, Xin Geng, Masashi Sugiyama
2020	A*	`conf`	Provably Consistent Partial-Label Learning. NeurIPS Lei Feng, Jiaqi Lv, Bo Han, Miao Xu, Gang Niu, Xin Geng, Bo An, Masashi Sugiyama
2020	J	`jnl`	Provably Consistent Partial-Label Learning. CoRR Lei Feng, Jiaqi Lv, Bo Han, Miao Xu, Gang Niu, Xin Geng, Bo An, Masashi Sugiyama
2020	J	`jnl`	Robust Multi-Label Learning with PRO Loss. IEEE Trans. Knowl. Data Eng. Miao Xu, Yufeng Li, Zhi-Hua Zhou
2020	A*	`conf`	SIGUA: Forgetting May Make Learning with Noisy Labels More Robust. ICML Bo Han, Gang Niu, Xingrui Yu, Quanming Yao, Miao Xu, Ivor W. Tsang, Masashi Sugiyama
2020	A*	`conf`	Trading Personalization for Accuracy: Data Debugging in Collaborative Filtering. NeurIPS Long Chen, Yuan Yao, Feng Xu, Miao Xu, Hanghang Tong
2019	A*	`conf`	Clipped Matrix Completion: A Remedy for Ceiling Effects. AAAI Takeshi Teshima, Miao Xu, Issei Sato, Masashi Sugiyama
2019	J	`jnl`	Revisiting Sample Selection Approach to Positive-Unlabeled Learning: Turning Unlabeled Data into Positive rather than Negative. CoRR Miao Xu, Bingcong Li, Gang Niu, Bo Han, Masashi Sugiyama
2018	A*	`conf`	Active Feature Acquisition with Supervised Matrix Completion. KDD Sheng-Jun Huang, Miao Xu, Ming-Kun Xie, Masashi Sugiyama, Gang Niu, Songcan Chen
2018	J	`jnl`	Active Feature Acquisition with Supervised Matrix Completion. CoRR Sheng-Jun Huang, Miao Xu, Ming-Kun Xie, Masashi Sugiyama, Gang Niu, Songcan Chen
2018	J	`jnl`	Clipped Matrix Completion: a Remedy for Ceiling Effects. CoRR Takeshi Teshima, Miao Xu, Issei Sato, Masashi Sugiyama
2018	J	`jnl`	Co-sampling: Training Robust Networks for Extremely Noisy Supervision. CoRR Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor W. Tsang, Masashi Sugiyama
2018	A*	`conf`	Co-teaching: Robust training of deep neural networks with extremely noisy labels. NeurIPS Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor W. Tsang, Masashi Sugiyama
2018	J	`jnl`	Matrix Co-completion for Multi-label Classification with Missing Features and Labels. CoRR Miao Xu, Gang Niu, Bo Han, Ivor W. Tsang, Zhi-Hua Zhou, Masashi Sugiyama
2018	J	`jnl`	Pumpout: A Meta Approach for Robustly Training Deep Neural Networks with Noisy Labels. CoRR Bo Han, Gang Niu, Jiangchao Yao, Xingrui Yu, Miao Xu, Ivor W. Tsang, Masashi Sugiyama
2017	A*	`conf`	Incomplete Label Distribution Learning. IJCAI Miao Xu, Zhi-Hua Zhou
2015	A*	`conf`	CUR Algorithm for Partially Observed Matrices. ICML Miao Xu, Rong Jin, Zhi-Hua Zhou
2014	J	`jnl`	CUR Algorithm for Partially Observed Matrices. CoRR Miao Xu, Rong Jin, Zhi-Hua Zhou
2013	A*	`conf`	Multi-Label Learning with PRO Loss. AAAI Miao Xu, Yufeng Li, Zhi-Hua Zhou
2013	—	`conf`	Speedup Matrix Completion with Side Information: Application to Multi-Label Learning. NIPS Miao Xu, Rong Jin, Zhi-Hua Zhou