Overview
Availability
- Dr Miao Xu is:
- Available for supervision
Qualifications
- Doctor of Philosophy, Nanjing University
Works
Search Professor Miao Xu’s works on UQ eSpace
2024
Journal Article
Designing unique and high-performance Al alloys via machine learning: mitigating data bias through active learning
Hu, Mingwei, Tan, Qiyang, Knibbe, Ruth, Xu, Miao, Liang, Guofang, Zhou, Jianxin, Xu, Jun, Jiang, Bin, Li, Xue, Ramajayam, Mahendra, Dorin, Thomas and Zhang, Ming-Xing (2024). Designing unique and high-performance Al alloys via machine learning: mitigating data bias through active learning. Computational Materials Science, 244 113204, 113204. doi: 10.1016/j.commatsci.2024.113204
2024
Journal Article
Mitigating the Impact of Inaccurate Feedback in Dynamic Learning-to-Rank: A Study of Overlooked Interesting Items
Zhang, Chenhao, Chen, Weitong, Zhang, Wei Emma and Xu, Miao (2024). Mitigating the Impact of Inaccurate Feedback in Dynamic Learning-to-Rank: A Study of Overlooked Interesting Items. ACM Transactions on Intelligent Systems and Technology. doi: 10.1145/3653983
2024
Conference Publication
Inspecting prediction confidence for detecting black-box backdoor attacks
Wang, Tong, Yao, Yuan, Xu, Feng, Xu, Miao, An, Shengwei and Wang, Ting (2024). Inspecting prediction confidence for detecting black-box backdoor attacks . Thirty-Eighth AAAI Conference on Artificial Intelligence, Vancouver, Canada, 20-27 February 2024. Washington, DC, United States: Association for the Advancement of Artificial Intelligence. doi: 10.1609/aaai.v38i1.27780
2024
Journal Article
Complementary to Multiple Labels: A Correlation-Aware Correction Approach
Gao, Yi, Xu, Miao and Zhang, Min-Ling (2024). Complementary to Multiple Labels: A Correlation-Aware Correction Approach. IEEE Transactions on Pattern Analysis and Machine Intelligence, PP, 1-13. doi: 10.1109/tpami.2024.3416384
2024
Conference Publication
Label-agnostic forgetting: a supervision-free unlearning in deep models
Shen, Shaofei, Zhang, Chenhao, Zhao, Yawen, Chen, Weitong, Bialkowski, Alina and Xu, Miao (2024). Label-agnostic forgetting: a supervision-free unlearning in deep models. 12th International Conference on Learning Representations, ICLR 2024, Vienna, Austria, 7-11 May 2024. Vienna, Austria: International Conference on Learning Representations, ICLR.
2024
Conference Publication
CaMU: Disentangling Causal Effects in Deep Model Unlearning
Shen, Shaofei, Zhang, Chenhao, Bialkowski, Alina, Chen, Weitong and Xu, Miao (2024). CaMU: Disentangling Causal Effects in Deep Model Unlearning. 2024 SIAM InternationalConference on Data Mining (SDM'24), Houston, TX United States, 18 - 20 April 2024. Philadelphia, PA United States: Society for Industrial and Applied Mathematics Publications. doi: 10.1137/1.9781611978032.89
2023
Journal Article
Recent applications of machine learning in alloy design: a review
Hu, Mingwei, Tan, Qiyang, Knibbe, Ruth, Xu, Miao, Jiang, Bin, Wang, Sen, Li, Xue and Zhang, Ming-Xing (2023). Recent applications of machine learning in alloy design: a review. Materials Science and Engineering: R: Reports, 155 100746, 100746. doi: 10.1016/j.mser.2023.100746
2023
Journal Article
Pre-training in medical data: a survey
Qiu, Yixuan, Lin, Feng, Chen, Weitong and Xu, Miao (2023). Pre-training in medical data: a survey. Machine Intelligence Research, 20 (2), 147-179. doi: 10.1007/s11633-022-1382-8
2023
Conference Publication
Death comes but why: an interpretable illness severity predictions in ICU
Shen, Shaofei, Xu, Miao, Yue, Lin, Boots, Robert and Chen, Weitong (2023). Death comes but why: an interpretable illness severity predictions in ICU. Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data, Nanjing, China, 11-13 August 2022. Heidelberg, Germany: Springer. doi: 10.1007/978-3-031-25158-0_6
2023
Conference Publication
A progressive sampling method for dual -node imbalanced learning with restricted data access
Qiu, Yixuan, Chen, Weitong and Xu, Miao (2023). A progressive sampling method for dual -node imbalanced learning with restricted data access. 23rd IEEE International Conference on Data Mining (IEEE ICDM), Shanghai, Peoples R China, 1-4 December 2023. Piscataway, NJ, United States: IEEE Computer Society. doi: 10.1109/ICDM58522.2023.00060
2023
Journal Article
On the robustness of average losses for partial-label learning
Lv, Jiaqi, Liu, Biao, Feng, Lei, Xu, Ning, Xu, Miao, An, Bo, Niu, Gang, Geng, Xin and Sugiyama, Masashi (2023). On the robustness of average losses for partial-label learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 46 (5), 1-15. doi: 10.1109/TPAMI.2023.3275249
2023
Book Chapter
Words can be confusing: stereotype bias removal in text classification at the word level
Shen, Shaofei, Zhang, Mingzhe, Chen, Weitong, Bialkowski, Alina and Xu, Miao (2023). Words can be confusing: stereotype bias removal in text classification at the word level. Advances in knowledge discovery and data mining. (pp. 99-111) edited by Hisashi Kashima, Tsuyoshi Ide and Wen-Chih Peng. Cham, Switzerland: Springer. doi: 10.1007/978-3-031-33383-5_8
2023
Conference Publication
Unbiased risk estimator to multi-labeled complementary label learning
Gao, Yi, Xu, Miao and Zhang, Min-Ling (2023). Unbiased risk estimator to multi-labeled complementary label learning. 32nd International Joint Conference on Artificial Intelligence (IJCAI), Macao, Peoples Republic of China, 19-25 August 2023. Freiburg, Germany: International Joint Conference on Artificial Intelligence. doi: 10.24963/ijcai.2023/415
2022
Conference Publication
Positive-unlabeled learning using random forests via recursive greedy risk minimization
Wilton, Jonathan, Koay, Abigail M. Y., Ko, Ryan K. L., Miao Xu and Ye, Nan (2022). Positive-unlabeled learning using random forests via recursive greedy risk minimization. 36th Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, United States, 29 November - 1 December 2022. New Orleans, LA, United States: Neural information processing systems foundation.
2022
Conference Publication
Fair Representation Learning: An Alternative to Mutual Information
Liu, Ji, Li, Zenan, Yao, Yuan, Xu, Feng, Ma, Xiaoxing, Xu, Miao and Tong, Hanghang (2022). Fair Representation Learning: An Alternative to Mutual Information. KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC United States, 14 - 18 August 2022. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3534678.3539302
2022
Conference Publication
Towards better generalization for neural network-based SAT solvers
Zhang, Chenhao, Zhang, Yanjun, Mao, Jeff, Chen, Weitong, Yue, Lin, Bai, Guangdong and Xu, Miao (2022). Towards better generalization for neural network-based SAT solvers. 26th Pacific-Asia Conference, PAKDD 2022, Chengdu, China, 16-19 May 2022. CHAM: Springer Science and Business Media Deutschland GmbH. doi: 10.1007/978-3-031-05936-0_16
2022
Journal Article
Personalized on-device e-health analytics with decentralized block coordinate descent
Ye, Guanhua, Yin, Hongzhi, Chen, Tong, Xu, Miao, Nguyen, Quoc Viet Hung and Song, Jiangning (2022). Personalized on-device e-health analytics with decentralized block coordinate descent. IEEE Journal of Biomedical and Health Informatics, 26 (6), 1-1. doi: 10.1109/JBHI.2022.3140455
2022
Conference Publication
What leads to arrhythmia: active causal representation learning of ECG classification
Shen, Shaofei, Chen, Weitong and Xu, Miao (2022). What leads to arrhythmia: active causal representation learning of ECG classification. 35th Australasian Joint Conference, AI 2022, Perth, WA, Australia, 5-8 December 2022. Cham, Switzerland: Springer Nature Switzerland. doi: 10.1007/978-3-031-22695-3_35
2022
Conference Publication
STCT: Spatial-temporal conv-transformer network for cardiac arrhythmias recognition
Qiu, Yixuan, Chen, Weitong, Yue, Lin, Xu, Miao and Zhu, Baofeng (2022). STCT: Spatial-temporal conv-transformer network for cardiac arrhythmias recognition. International Conference on Advanced Data Mining and Applications, Sydney, NSW, Australia, 2-4 February 2022. Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-95405-5_7
2022
Conference Publication
A boosting algorithm for training from only unlabeled data
Zhao, Yawen, Yue, Lin and Xu, Miao (2022). A boosting algorithm for training from only unlabeled data. 18th International Conference on Advanced Data Mining and Applications, ADMA 2022, Brisbane, QLD, Australia, 28-30 November 2022. Heidelberg, Germany: Springer. doi: 10.1007/978-3-031-22137-8_34
Funding
Current funding
Supervision
Availability
- Dr Miao Xu is:
- Available for supervision
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Available projects
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Detecting Key Concepts from Low-Quality Data for Better Decision
Recruiting students with strong academic background and interest in weakly supervised machine learning.
Supervision history
Current supervision
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Doctor Philosophy
Fairness-aware Personal Medicine: From Disease Diagnosis to Treatment
Principal Advisor
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Doctor Philosophy
High-stakes Decision Making with Weakly Supervised Data
Principal Advisor
Other advisors: Dr Nan Ye
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Doctor Philosophy
Real-time Analytics on Urban Trajectory Data for Road Traffic Management
Principal Advisor
Other advisors: Associate Professor Jiwon Kim
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Doctor Philosophy
Domain Adaptation in Causality Views
Principal Advisor
Other advisors: Dr Alina Bialkowski
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Doctor Philosophy
Deep learning methods for imbalanced medical multivariate time series data
Principal Advisor
-
Doctor Philosophy
Machine Learning for Cyber Security
Principal Advisor
Other advisors: Professor Ryan Ko
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Doctor Philosophy
Weakly Supervised Learning for Mental Health
Principal Advisor
Other advisors: Dr Laura Ferris
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Doctor Philosophy
Efficient Methods for Automating Reconstruction of Provenance and Cryptocurrency Networks for Crime Attribution
Associate Advisor
Other advisors: Professor Ryan Ko
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Doctor Philosophy
Knowledge Graph-based Conversational Recommender Systems
Associate Advisor
Other advisors: Professor Hongzhi Yin
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Doctor Philosophy
Demand Profile Modeling for Low-Voltage Distribution System
Associate Advisor
Other advisors: Associate Professor Archie Chapman
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Doctor Philosophy
Federated Graph Neural Network-based Recommender Systems
Associate Advisor
Other advisors: Professor Hongzhi Yin
Completed supervision
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2023
Doctor Philosophy
From Cloud to Device: Transforming Recommender Systems for On-Device Deployment
Associate Advisor
Other advisors: Professor Hongzhi Yin
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2023
Doctor Philosophy
Decentralized On-device Machine Learning and Unlearning for IoT Collaboration
Associate Advisor
Other advisors: Professor Hongzhi Yin
Media
Enquiries
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