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
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, 16 (1) 5, 1-26. 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
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
2024
Conference Publication
What makes partial-label learning algorithms effective?
Lv, Jiaqi, Liu, Yangfan, Xia, Shiyu, Xu, Ning, Xu, Miao, Niu, Gang, Zhang, Min-Ling, Sugiyama, Masashi and Geng, Xin (2024). What makes partial-label learning algorithms effective?. 38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, BC, Canada, 10-15 December 2024. San Mateo, CA, United States: Morgan Kaufmann Publishers.
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
Machine Unlearning: Challenges in Data Quality and Access
Xu, Miao (2024). Machine Unlearning: Challenges in Data Quality and Access. 33rd International Joint Conference on Artificial Intelligence (IJCAI), Jeju, South Korea, 3-9 August 2024. Freiburg, Germany: IJCAI. doi: 10.24963/ijcai.2024/987
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
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) 10122995, 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
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, China, 1-4 December 2023. Piscataway, NJ United States: IEEE Computer Society. doi: 10.1109/ICDM58522.2023.00060
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. doi: 10.52202/068431-1747
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
Conference Publication
Improving traffic load prediction with multi-modality: a case study of Brisbane
Tran, Khai Phan, Chen, Weitong and Xu, Miao (2022). Improving traffic load prediction with multi-modality: a case study of Brisbane. 34th Australasian Joint Conference, AI 2021, Sydney, NSW Australia, 2-4 February 2022. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-97546-3_21
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
2022
Conference Publication
Investigating active positive-unlabeled learning with deep networks
Han, Kun, Chen, Weitong and Xu, Miao (2022). Investigating active positive-unlabeled learning with deep networks. Australasian Joint Conference on Artificial Intelligence (AI), Electr Network, 2-4 February 2022. Cham, Switzerland: Springer Nature Switzerland. doi: 10.1007/978-3-030-97546-3_49
2022
Conference Publication
ESTD: Empathy Style Transformer with Discriminative Mechanism
Zhang, Mingzhe, Yue, Lin and Xu, Miao (2022). ESTD: Empathy Style Transformer with Discriminative Mechanism. 18th International Conference, ADMA 2022, Brisbane, QLD, Australia, 28-30 November 2022. Cham, Switzerland: Springer. doi: 10.1007/978-3-031-22137-8_5
Funding
Current funding
Supervision
Availability
- Dr Miao Xu is:
- Available for supervision
Looking for a supervisor? Read our advice on how to choose a supervisor.
Available projects
-
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
Weakly Supervised Learning for Mental Health
Principal Advisor
Other advisors: Dr Laura Ferris
-
Doctor Philosophy
Multi-Modal Perception for Context-Aware Systems
Principal Advisor
Other advisors: Dr Yujun Cai
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Doctor Philosophy
High-stakes Decision Making with Weakly Supervised Data
Principal Advisor
Other advisors: Dr Nan Ye
-
Doctor Philosophy
Domain Adaptation in Causality Views
Principal Advisor
Other advisors: Dr Alina Bialkowski
-
Doctor Philosophy
Deep learning methods for imbalanced medical multivariate time series data
Principal Advisor
-
Doctor Philosophy
Trustworthy Learning from Irregular Time Series: Robust Modeling and Interpretable Decision-Making
Principal Advisor
Other advisors: Professor Ryan Ko
-
Doctor Philosophy
Towards knowledge discovery from imperfect and evolving data
Principal Advisor
Other advisors: Associate Professor Xin Yu
-
-
Doctor Philosophy
Understanding Human Intention and Performance
Associate Advisor
Other advisors: Dr Heming Du, Associate Professor Xin Yu
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Doctor Philosophy
Multi-Modal Perception for Context-Aware Systems
Associate Advisor
Other advisors: Dr Yujun Cai
-
Doctor Philosophy
Integrating Deep Learning and Remote Sensing for Precision Agriculture in Staple Crops
Associate Advisor
Other advisors: Associate Professor Xin Yu
-
Doctor Philosophy
Understanding Human Movements and Sport Performance Analysis
Associate Advisor
Other advisors: Associate Professor Xin Yu
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Doctor Philosophy
Analysis of Machine Learning Systems
Associate Advisor
Other advisors: Dr Naipeng Dong
-
Doctor Philosophy
Combating evolving deceptive fake visual information through deepfake detection
Associate Advisor
Other advisors: Associate Professor Xin Yu
-
-
Doctor Philosophy
Efficient Methods for Automating Reconstruction of Provenance and Cryptocurrency Networks for Crime Attribution
Associate Advisor
Other advisors: Professor Ryan Ko
-
Doctor Philosophy
Compressed Video Restoration
Associate Advisor
Other advisors: Dr Heming Du, Associate Professor Xin Yu
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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
Multimodal foundation model design and analysis
Associate Advisor
Other advisors: Associate Professor Xin Yu, Dr Heming Du
Completed supervision
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2026
Doctor Philosophy
Data-Limited Class Unlearning: from Methodology to Evaluation
Principal Advisor
-
2026
Doctor Philosophy
A Study on Map-Matching on Wireless Traffic Sensor Data
Principal Advisor
Other advisors: Associate Professor Jiwon Kim
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2026
Doctor Philosophy
Robust learning algorithms for weakly supervised data
Associate Advisor
Other advisors: Dr Nan Ye
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2025
Doctor Philosophy
Secure Cross-device Federated Recommender Systems
Associate Advisor
Other advisors: Professor Hongzhi Yin
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2024
Doctor Philosophy
Federated Graph Neural Network-based Recommender Systems
Associate Advisor
Other advisors: Professor Hongzhi Yin
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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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