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2024 Conference Publication Decentralized collaborative learning with adaptive reference data for on-device POI recommendationZheng, Ruiqi, Qu, Liang, Chen, Tong, Cui, Lizhen, Shi, Yuhui and Yin, Hongzhi (2024). Decentralized collaborative learning with adaptive reference data for on-device POI recommendation. WWW '24: The ACM Web Conference 2024, Singapore, 13 - 17 May 2024. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3589334.3645696 |
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2024 Conference Publication Unraveling the ‘Anomaly’ in time series anomaly detection: a self-supervised tri-domain solutionSun, Yuting, Pang, Guansong, Ye, Guanhua, Chen, Tong, Hu, Xia and Yin, Hongzhi (2024). Unraveling the ‘Anomaly’ in time series anomaly detection: a self-supervised tri-domain solution. 2024 IEEE 40th International Conference on Data Engineering (ICDE), Utrecht, Netherlands, 13-16 May 2024. Piscataway, NJ, United States: IEEE. doi: 10.1109/icde60146.2024.00080 |
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2024 Conference Publication On-device recommender systems: a tutorial on the new-generation recommendation paradigmYin, Hongzhi, Chen, Tong, Qu, Liang and Cui, Bin (2024). On-device recommender systems: a tutorial on the new-generation recommendation paradigm. 33rd ACM Web Conference, WWW 2024, Singapore, 13 - 17 May 2024. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3589335.3641250 |
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2024 Journal Article Variational counterfactual prediction under runtime domain corruptionWen, Hechuan, Chen, Tong, Chai, Li Kheng, Sadiq, Shazia, Gao, Junbin and Yin, Hongzhi (2024). Variational counterfactual prediction under runtime domain corruption. IEEE Transactions on Knowledge and Data Engineering, 36 (5) 10271745, 2271-2284. doi: 10.1109/tkde.2023.3321893 |
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2024 Conference Publication Budgeted embedding table for recommender systemsQu, Yunke, Chen, Tong, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2024). Budgeted embedding table for recommender systems. 17th ACM International Conference on Web Search and Data Mining (WSDM), Merida, Mexico, 4-8 March 2024. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3616855.3635778 |
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2024 Journal Article Time interval-enhanced graph neural network for shared-account cross-domain sequential recommendationGuo, Lei, Zhang, Jinyu, Tang, Li, Chen, Tong, Zhu, Lei and Yin, Hongzhi (2024). Time interval-enhanced graph neural network for shared-account cross-domain sequential recommendation. IEEE Transactions on Neural Networks and Learning Systems, 35 (3), 4002-4016. doi: 10.1109/tnnls.2022.3201533 |
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2024 Journal Article XSimGCL: towards extremely simple graph contrastive learning for recommendationYu, Junliang, Xia, Xin, Chen, Tong, Cui, Lizhen, Hung, Nguyen Quoc Viet and Yin, Hongzhi (2024). XSimGCL: towards extremely simple graph contrastive learning for recommendation. IEEE Transactions on Knowledge and Data Engineering, 36 (2), 913-926. doi: 10.1109/tkde.2023.3288135 |
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2024 Journal Article Self-supervised learning for recommender systems: a surveyYu, Junliang, Yin, Hongzhi, Xia, Xin, Chen, Tong, Li, Jundong and Huang, Zi (2024). Self-supervised learning for recommender systems: a survey. IEEE Transactions on Knowledge and Data Engineering, 36 (1), 335-355. doi: 10.1109/tkde.2023.3282907 |
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2023 Conference Publication Learning compact compositional embeddings via regularized pruning for recommendationLiang, Xurong, Chen, Tong, Nguyen, Quoc Viet Hung, Li, Jianxin and Yin, Hongzhi (2023). Learning compact compositional embeddings via regularized pruning for recommendation. 23rd IEEE International Conference on Data Mining (IEEE ICDM), Shanghai, China, 1-4 December 2023. Los Alamitos, CA United States: IEEE. doi: 10.1109/icdm58522.2023.00047 |
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2023 Conference Publication To predict or to reject: causal effect estimation with uncertainty on networked dataWen, Hechuan, Chen, Tong, Chai, Li Kheng, Sadiq, Shazia, Zheng, Kai and Yin, Hongzhi (2023). To predict or to reject: causal effect estimation with uncertainty on networked data. 23rd IEEE International Conference on Data Mining (IEEE ICDM), Shanghai, China, 1 - 4 December 2023. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/icdm58522.2023.00184 |
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2023 Journal Article Heterogeneous collaborative learning for personalized healthcare analytics via messenger distillationYe, Guanhua, Chen, Tong, Li, Yawen, Cui, Lizhen, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2023). Heterogeneous collaborative learning for personalized healthcare analytics via messenger distillation. IEEE Journal of Biomedical and Health Informatics, 27 (11), 5249-5259. doi: 10.1109/jbhi.2023.3247463 |
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2023 Conference Publication Self-supervised dynamic hypergraph recommendation based on hyper-relational knowledge graphLiu, Yi, Xuan, Hongrui, Li, Bohan, Wang, Meng, Chen, Tong and Yin, Hongzhi (2023). Self-supervised dynamic hypergraph recommendation based on hyper-relational knowledge graph. 32nd ACM International Conference on Information and Knowledge Management (CIKM), Birmingham, United States, 21-25 October 2023. New York, NY, United States: ACM. doi: 10.1145/3583780.3615054 |
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2023 Conference Publication Semantic-aware node synthesis for imbalanced heterogeneous information networksGao, Xinyi, Zhang, Wentao, Chen, Tong, Yu, Junliang, Nguyen, Hung Quoc Viet and Yin, Hongzhi (2023). Semantic-aware node synthesis for imbalanced heterogeneous information networks. 32nd ACM International Conference on Information and Knowledge Management, Birmingham, United Kingdom, 21–25 October 2023. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3583780.3615055 |
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2023 Conference Publication Continuous input embedding size search for recommender systemsQu, Yunke, Chen, Tong, Zhao, Xiangyu, Cui, Lizhen, Zheng, Kai and Yin, Hongzhi (2023). Continuous input embedding size search for recommender systems. The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, Taipei, Taiwan, 23-27 July 2023. New York, NY, United States: ACM. doi: 10.1145/3539618.3591653 |
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2023 Conference Publication DREAM: adaptive reinforcement learning based on attention mechanism for temporal knowledge graph reasoningZheng, Shangfei, Yin, Hongzhi, Chen, Tong, Nguyen, Quoc Viet Hung, Chen, Wei and Zhao, Lei (2023). DREAM: adaptive reinforcement learning based on attention mechanism for temporal knowledge graph reasoning. 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, Taipei, Taiwan, 23–27 July 2023. New York, NY, United States: ACM. doi: 10.1145/3539618.3591671 |
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2023 Conference Publication Model-agnostic decentralized collaborative learning for on-device POI recommendationLong, Jing, Chen, Tong, Nguyen, Quoc Viet Hung, Xu, Guandong, Zheng, Kai and Yin, Hongzhi (2023). Model-agnostic decentralized collaborative learning for on-device POI recommendation. 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, Taipei, Taiwan, 23-27 July 2023. New York, NY, United States: ACM. doi: 10.1145/3539618.3591733 |
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2023 Conference Publication KGA: A General Machine Unlearning Framework Based on Knowledge Gap AlignmentWang, Lingzhi, Chen, Tong, Yuan, Wei, Zeng, Xingshan, Wong, Kam-Fai and Yin, Hongzhi (2023). KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment. 61st Annual Meeting of the Association for Computational Linguistics, Toronto, Canada, 9 - 14 July 2023. Stroudsburg, PA United States: Association for Computational Linguistics. |
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2023 Journal Article Spatial-temporal meta-path guided explainable crime predictionSun, Yuting, Chen, Tong and Yin, Hongzhi (2023). Spatial-temporal meta-path guided explainable crime prediction. World Wide Web, 26 (4), 2237-2263. doi: 10.1007/s11280-023-01137-3 |
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2023 Journal Article Reinforcement learning-enhanced shared-account cross-domain sequential recommendationGuo, Lei, Zhang, Jinyu, Chen, Tong, Wang, Xinhua and Yin, Hongzhi (2023). Reinforcement learning-enhanced shared-account cross-domain sequential recommendation. IEEE Transactions on Knowledge and Data Engineering, 35 (7), 7397-7411. doi: 10.1109/tkde.2022.3185101 |
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2023 Journal Article DeHIN: a decentralized framework for embedding large-scale heterogeneous information networksImran, Mubashir, Yin, Hongzhi, Chen, Tong, Huang, Zi and Zheng, Kai (2023). DeHIN: a decentralized framework for embedding large-scale heterogeneous information networks. IEEE Transactions on Knowledge and Data Engineering, 35 (4), 3645-3657. doi: 10.1109/TKDE.2022.3141951 |
