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2025 Journal Article PTF-FSR: a parameter transmission-free federated sequential recommender systemYuan, Wei, Yang, Chaoqun, Qu, Liang, Hung, Nguyen Quoc Viet, Ye, Guanhua and Yin, Hongzhi (2025). PTF-FSR: a parameter transmission-free federated sequential recommender system. ACM Transactions on Information Systems, 43 (2) 52, 1-24. doi: 10.1145/3708344 |
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2025 Journal Article Certified unlearning for federated recommendationHuynh, Thanh Trung, Nguyen, Trong Bang, Nguyen, Thanh Toan, Nguyen, Phi Le, Yin, Hongzhi, Nguyen, Quoc Viet Hung and Nguyen, Thanh Tam (2025). Certified unlearning for federated recommendation. ACM Transactions on Information Systems, 43 (2) 6419, 1-29. doi: 10.1145/3706419 |
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2025 Journal Article Privacy-preserving explainable AI: a surveyNguyen, Thanh Tam, Huynh, Thanh Trung, Ren, Zhao, Nguyen, Thanh Toan, Nguyen, Phi Le, Yin, Hongzhi and Nguyen, Quoc Viet Hung (2025). Privacy-preserving explainable AI: a survey. Science China-Information Sciences, 68 (1) 111101. doi: 10.1007/s11432-024-4123-4 |
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2025 Journal Article ZhiFangDanTai: Fine-tuning Graph-based Retrieval-Augmented Generation Model for Traditional Chinese Medicine FormulaZhang, Zixuan, Hao, Bowen, Li, Yingjie and Yin, Hongzhi (2025). ZhiFangDanTai: Fine-tuning Graph-based Retrieval-Augmented Generation Model for Traditional Chinese Medicine Formula. IEEE Journal of Biomedical and Health Informatics, PP (99), 1-14. doi: 10.1109/jbhi.2025.3607819 |
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2025 Journal Article Handling low homophily in recommender systems with partitioned graph transformerNguyen, Thanh Tam, Nguyen, Thanh Toan, Weidlich, Matthias, Jo, Jun, Nguyen, Quoc Viet Hung, Yin, Hongzhi and Liew, Alan Wee-Chung (2025). Handling low homophily in recommender systems with partitioned graph transformer. IEEE Transactions on Knowledge and Data Engineering, 37 (1), 334-350. doi: 10.1109/tkde.2024.3485880 |
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2025 Conference Publication Multi-task learning of heterogeneous hypergraph representations in LBSNsNguyen, Dong Duc Anh, Nguyen, Minh Hieu, Nguyen, Phi Le, Jo, Jun, Yin, Hongzhi and Nguyen, Thanh Tam (2025). Multi-task learning of heterogeneous hypergraph representations in LBSNs. 20th International Conference, ADMA 2024, Sydney, NSW, Australia, 3 - 5 December 2024. Heidelberg, Germany: Springer. doi: 10.1007/978-981-96-0821-8_11 |
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2025 Journal Article Teaching MLPs to Master Heterogeneous Graph-Structured Knowledge for Efficient and Accurate InferenceLiu, Yunhui, Gao, Xinyi, He, Tieke, Zhao, Jianhua and Yin, Hongzhi (2025). Teaching MLPs to Master Heterogeneous Graph-Structured Knowledge for Efficient and Accurate Inference. IEEE Transactions on Knowledge and Data Engineering, PP (99), 1-13. doi: 10.1109/tkde.2025.3589596 |
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2025 Journal Article PUMA: efficient continual graph learning for node classification with graph condensationLiu, Yilun, Qiu, Ruihong, Tang, Yanran, Yin, Hongzhi and Huang, Zi (2025). PUMA: efficient continual graph learning for node classification with graph condensation. IEEE Transactions on Knowledge and Data Engineering, 37 (1), 449-461. doi: 10.1109/tkde.2024.3485691 |
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2025 Conference Publication Hyperbolic adversarial learning for personalized item recommendationZhang, Aoran, Yu, Yonghong, Xu, Gongyou, Gao, Rong, Zhang, Li, Gao, Shang and Yin, Hongzhi (2025). Hyperbolic adversarial learning for personalized item recommendation. 29th International Conference on Database Systems for Advanced Applications, DASFAA 2024, Gifu, Japan, 2-5 July 2024. Singapore: Springer Nature Singapore. doi: 10.1007/978-981-97-5555-4_20 |
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2025 Journal Article Automated Prompting for Non-Overlapping Cross-Domain Sequential RecommendationGuo, Lei, Wang, Chunxiao, Wang, Xinhua, Zhu, Lei and Yin, Hongzhi (2025). Automated Prompting for Non-Overlapping Cross-Domain Sequential Recommendation. IEEE Transactions on Knowledge and Data Engineering, PP (99), 1-14. doi: 10.1109/tkde.2025.3589721 |
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2025 Conference Publication Disentangled representations for cross-domain recommendation via heterogeneous graph contrastive learningLiu, Xinyue, Li, Bohan, Chen, Yijun, Li, Xiaoxue, Xu, Shuai and Yin, Hongzhi (2025). Disentangled representations for cross-domain recommendation via heterogeneous graph contrastive learning. 29th International Conference on Database Systems for Advanced Applications, DASFAA 2024, Gifu, Japan, 2-5 July 2024. Singapore: Springer Nature Singapore. doi: 10.1007/978-981-97-5555-4_3 |
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2025 Book Chapter Resource-Efficient Model Deployment for Enterprise AIChen, Tong, Yu, Junliang and Yin, Hongzhi (2025). Resource-Efficient Model Deployment for Enterprise AI. Enterprise AI. (pp. 3-23) Cham: Springer Nature Switzerland. doi: 10.1007/978-3-032-01940-0_1 |
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2024 Journal Article A dual benchmarking study of facial forgery and facial forensicsPham, Minh Tam, Huynh, Thanh Trung, Nguyen, Thanh Tam, Nguyen, Thanh Toan, Nguyen, Thanh Thi, Jo, Jun, Yin, Hongzhi and Hung Nguyen, Quoc Viet (2024). A dual benchmarking study of facial forgery and facial forensics. CAAI Transactions on Intelligence Technology, 9 (6), 1377-1397. doi: 10.1049/cit2.12362 |
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2024 Journal Article Reliable node similarity matrix guided contrastive graph clusteringLiu, Yunhui, Gao, Xinyi, He, Tieke, Zheng, Tao, Zhao, Jianhua and Yin, Hongzhi (2024). Reliable node similarity matrix guided contrastive graph clustering. IEEE Transactions on Knowledge and Data Engineering, 36 (12), 9123-9135. doi: 10.1109/tkde.2024.3435887 |
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2024 Journal Article Hyperbolic translation-based sequential recommendationYu, Yonghong, Zhang, Aoran, Zhang, Li, Gao, Rong, Gao, Shang and Yin, Hongzhi (2024). Hyperbolic translation-based sequential recommendation. IEEE Transactions on Computational Social Systems, 11 (6), 7467-7483. doi: 10.1109/tcss.2024.3409711 |
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2024 Journal Article Multi-level graph knowledge contrastive learningYang, Haoran, Wang, Yuhao, Zhao, Xiangyu, Chen, Hongxu, Yin, Hongzhi, Li, Qing and Xu, Guandong (2024). Multi-level graph knowledge contrastive learning. IEEE Transactions on Knowledge and Data Engineering, 36 (12), 8829-8841. doi: 10.1109/TKDE.2024.3466530 |
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2024 Conference Publication Watermarking recommender systemsZhang, Sixiao, Long, Cheng, Yuan, Wei, Chen, Hongxu and Yin, Hongzhi (2024). Watermarking recommender systems. 33rd ACM International Conference on Information and Knowledge Management (CIKM), Boise, ID USA, 21-25 October 2024. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3627673.3679617 |
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2024 Conference Publication Scalable dynamic embedding size search for streaming recommendationQu, Yunke, Qu, Liang, Chen, Tong, Zhao, Xiangyu, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2024). Scalable dynamic embedding size search for streaming recommendation. 33rd ACM International Conference on Information and Knowledge Management (CIKM), Boise, ID USA, 21-25 October 2024. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3627673.3679638 |
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2024 Conference Publication Physics-guided active sample reweighting for urban flow predictionJiang, Wei, Chen, Tong, Ye, Guanhua, Zhang, Wentao, Cui, Lizhen, Huang, Zi and Yin, Hongzhi (2024). Physics-guided active sample reweighting for urban flow prediction. 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: 10.1145/3627673.3679738 |
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2024 Conference Publication Preference prototype-aware learning for universal cross-domain recommendationZhang, Yuxi, Zhang, Ji, Xu, Feiyang, Chen, Lvying, Li, Bohan, Guo, Lei and Yin, Hongzhi (2024). Preference prototype-aware learning for universal cross-domain recommendation. 33rd ACM International Conference on Information and Knowledge Management (CIKM), Boise, ID USA, 21-25 October 2024. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3627673.3679774 |
