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2025 Conference Publication Understanding Why Large Language Models Can Be Ineffective in Time Series Analysis: The Impact of Modality AlignmentZheng, Liangwei Nathan, Dong, Chang, Zhang, Wei Emma, Yue, Lin, Xu, Miao, Maennel, Olaf and Chen, Weitong (2025). Understanding Why Large Language Models Can Be Ineffective in Time Series Analysis: The Impact of Modality Alignment. New York, NY, USA: ACM. doi: 10.1145/3711896.3737169 |
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2025 Conference Publication Cross-view isolated sign language recognition challenge: design, results and future researchShen, Xin, Du, Heming, Xu, Miao, Liu, Miaomiao and Yu, Xin (2025). Cross-view isolated sign language recognition challenge: design, results and future research. WWW '25: The ACM Web Conference 2025, Sydney, NSW Australia, 28 April-2 May 2025. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3701716.3717522 |
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2024 Conference Publication Mining irregular time series data with noisy labels: A risk estimation approachHan, Kun, Koay, Abigail, Ko, Ryan K. L., Chen, Weitong and Xu, Miao (2024). Mining irregular time series data with noisy labels: A risk estimation approach. 35th Australasian Database Conference, ADC 2024, Gold Coast, QLD Australia, 16–18 December 2024. Singapore: Springer. doi: 10.1007/978-981-96-1242-0_22 |
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2024 Conference Publication Emotionally guided symbolic music generation using diffusion models: the AGE-DM approachZhang, Mingzhe, Ferris, Laura J., Yue, Lin and Xu, Miao (2024). Emotionally guided symbolic music generation using diffusion models: the AGE-DM approach. MMAsia '24, Auckland, New Zealand, 3 - 6 December 2024. New York, NY, United States: ACM. doi: 10.1145/3696409.3700289 |
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2024 Conference Publication Irregularity-informed time series analysis: adaptive modelling of spatial and temporal dynamicsZheng, Liangwei Nathan, Li, Zhengyang, Dong, Chang George, Zhang, Wei Emma, Yue, Lin, Xu, Miao, Maennel, Olaf and Chen, Weitong (2024). Irregularity-informed time series analysis: adaptive modelling of spatial and temporal dynamics. 33rd ACM International Conference on Information and Knowledge Management (CIKM), Boise, ID, United States, 21-25 October 2024. New York, United States: Association for Computing Machinery. doi: 10.1145/3627673.3679716 |
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2024 Conference Publication Unlearning From Weakly Supervised LearningTang, Yi, Gao, Yi, Luo, Yong-Gang, Yang, Ju-Cheng, Xu, Miao and Zhang, Min-Ling (2024). Unlearning From Weakly Supervised Learning. 33rd International Joint Conference on Artificial Intelligence (IJCAI), Jeju, South Korea, 3-9 August 2024. Freiburg, Germany: IJCAI. doi: 10.24963/ijcai.2024/553 |
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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 |
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2024 Conference Publication CaMU: Disentangling Causal Effects in Deep Model UnlearningShen, 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 |
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2024 Conference Publication Machine Unlearning: Challenges in Data Quality and AccessXu, 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 |
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2024 Conference Publication Label-agnostic forgetting: a supervision-free unlearning in deep modelsShen, 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. |
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2023 Conference Publication A progressive sampling method for dual -node imbalanced learning with restricted data accessQiu, 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 |
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2023 Conference Publication Unbiased risk estimator to multi-labeled complementary label learningGao, 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 |
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2023 Conference Publication Death comes but why: an interpretable illness severity predictions in ICUShen, 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 |
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2022 Conference Publication Positive-unlabeled learning using random forests via recursive greedy risk minimizationWilton, 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. |
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2022 Conference Publication Fair Representation Learning: An Alternative to Mutual InformationLiu, 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 |
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2022 Conference Publication Towards better generalization for neural network-based SAT solversZhang, 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 |
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2022 Conference Publication Improving traffic load prediction with multi-modality: a case study of BrisbaneTran, 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 |
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2022 Conference Publication What leads to arrhythmia: active causal representation learning of ECG classificationShen, 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 |
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2022 Conference Publication STCT: Spatial-temporal conv-transformer network for cardiac arrhythmias recognitionQiu, 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 |
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2022 Conference Publication A boosting algorithm for training from only unlabeled dataZhao, 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 |
