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2024

Conference Publication

Hate speech detection with generalizable target-aware fairness

Chen, Tong, Wang, Danny, Liang, Xurong, Risius, Marten, Demartini, Gianluca and Yin, Hongzhi (2024). Hate speech detection with generalizable target-aware fairness. KDD '24: 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, Spain, 25-29 August 2024. New York, NY, United States: ACM. doi: 10.1145/3637528.3671821

Hate speech detection with generalizable target-aware fairness

2024

Conference Publication

Unveiling vulnerabilities of contrastive recommender systems to poisoning attacks

Wang, Zongwei, Yu, Junliang, Gao, Min, Yin, Hongzhi, Cui, Bin and Sadiq, Shazia (2024). Unveiling vulnerabilities of contrastive recommender systems to poisoning attacks. 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, Spain, 25-29 August 2024. New York, NY, United States: ACM. doi: 10.1145/3637528.3671795

Unveiling vulnerabilities of contrastive recommender systems to poisoning attacks

2024

Conference Publication

Diffusion-based cloud-edge-device collaborative learning for next POI recommendations

Long, Jing, Ye, Guanhua, Chen, Tong, Wang, Yang, Wang, Meng and Yin, Hongzhi (2024). Diffusion-based cloud-edge-device collaborative learning for next POI recommendations. 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, Spain, 25-29 August 2024. New York, NY, United States: ACM. doi: 10.1145/3637528.3671743

Diffusion-based cloud-edge-device collaborative learning for next POI recommendations

2024

Conference Publication

Graph condensation for open-world graph learning

Gao, Xinyi, Chen, Tong, Zhang, Wentao, Li, Yayong, Sun, Xiangguo and Yin, Hongzhi (2024). Graph condensation for open-world graph learning. KDD '24: 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, Spain, 25-29 August 2024. New York, NY, United States: ACM. doi: 10.1145/3637528.3671917

Graph condensation for open-world graph learning

2024

Conference Publication

Lightweight embeddings for graph collaborative filtering

Liang, Xurong, Chen, Tong, Cui, Lizhen, Wang, Yang, Wang, Meng and Yin, Hongzhi (2024). Lightweight embeddings for graph collaborative filtering. SIGIR '24: 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, Washington, DC, United States, 14-18 July 2024. New York, NY, United States: ACM. doi: 10.1145/3626772.3657820

Lightweight embeddings for graph collaborative filtering

2024

Conference Publication

Poisoning decentralized collaborative recommender system and its countermeasures

Zheng, Ruiqi, Qu, Liang, Chen, Tong, Zheng, Kai, Shi, Yuhui and Yin, Hongzhi (2024). Poisoning decentralized collaborative recommender system and its countermeasures. SIGIR 2024: The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, Washington, DC, United States, 14-18 July 2024. New York, United States: Association for Computing Machinery. doi: 10.1145/3626772.3657814

Poisoning decentralized collaborative recommender system and its countermeasures

2024

Conference Publication

CaseLink: inductive graph learning for legal case retrieval

Tang, Yanran, Qiu, Ruihong, Yin, Hongzhi, Li, Xue and Huang, Zi (2024). CaseLink: inductive graph learning for legal case retrieval. 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, Washington, DC, United States, 14-18 July 2024. New York, NY, United States: ACM. doi: 10.1145/3626772.3657693

CaseLink: inductive graph learning for legal case retrieval

2024

Conference Publication

On-device recommender systems: a tutorial on the new-generation recommendation paradigm

Yin, 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

On-device recommender systems: a tutorial on the new-generation recommendation paradigm

2024

Conference Publication

Accelerating scalable graph neural network inference with node-adaptive propagation

Gao, Xinyi, Zhang, Wentao, Yu, Junliang, Shao, Yingxia, Nguyen, Quoc Viet Hung, Cui, Bin and Yin, Hongzhi (2024). Accelerating scalable graph neural network inference with node-adaptive propagation. 2024 IEEE 40th International Conference on Data Engineering (ICDE), Utrecht, Netherlands, 13-16 May 2024. Piscataway, NJ, United States: IEEE. doi: 10.1109/icde60146.2024.00236

Accelerating scalable graph neural network inference with node-adaptive propagation

2024

Conference Publication

Towards personalized privacy: user-governed data contribution for federated recommendation

Qu, Liang, Yuan, Wei, Zheng, Ruiqi, Cui, Lizhen, Shi, Yuhui and Yin, Hongzhi (2024). Towards personalized privacy: user-governed data contribution for federated recommendation. WWW '24: The ACM Web Conference 2024, Singapore, 13 - 17 May 2024. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3589334.3645690

Towards personalized privacy: user-governed data contribution for federated recommendation

2024

Conference Publication

Challenging low homophily in social recommendation

Jiang, Wei, Gao, Xinyi, Xu, Guandong, Chen, Tong and Yin, Hongzhi (2024). Challenging low homophily in social recommendation. WWW '24: The ACM Web Conference 2024, Singapore, 13-17 May 2024. New York, United States: Association for Computing Machinery. doi: 10.1145/3589334.3645460

Challenging low homophily in social recommendation

2024

Conference Publication

Physical trajectory inference attack and defense in decentralized POI recommendation

Long, Jing, Chen, Tong, Ye, Guanhua, Zheng, Kai, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2024). Physical trajectory inference attack and defense in decentralized POI recommendation. WWW '24: The ACM Web Conference 2024, Singapore, 13 - 17 May 2024. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3589334.3645410

Physical trajectory inference attack and defense in decentralized POI recommendation

2024

Conference Publication

Graph condensation for inductive node representation learning

Gao, Xinyi, Chen, Tong, Zang, Yilong, Zhang, Wentao, Hung Nguyen, Quoc Viet, Zheng, Kai and Yin, Hongzhi (2024). Graph condensation for inductive node representation learning. 2024 IEEE 40th International Conference on Data Engineering (ICDE), Utrecht, Netherlands, 13-16 May 2024. Piscataway, NJ, United States: IEEE. doi: 10.1109/icde60146.2024.00237

Graph condensation for inductive node representation learning

2024

Conference Publication

Decentralized collaborative learning with adaptive reference data for on-device POI recommendation

Zheng, 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

Decentralized collaborative learning with adaptive reference data for on-device POI recommendation

2024

Conference Publication

HeteFedRec: federated recommender systems with model heterogeneity

Yuan, Wei, Qu, Liang, Cui, Lizhen, Tong, Yongxin, Zhou, Xiaofang and Yin, Hongzhi (2024). HeteFedRec: federated recommender systems with model heterogeneity. 2024 IEEE 40th International Conference on Data Engineering (ICDE), Utrecht, Netherlands, 13-16 May 2024. Piscataway, NJ, United States: IEEE. doi: 10.1109/icde60146.2024.00109

HeteFedRec: federated recommender systems with model heterogeneity

2024

Conference Publication

Prompt-enhanced federated content representation learning for cross-domain recommendation

Guo, Lei, Lu, Ziang, Yu, Junliang, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2024). Prompt-enhanced federated content representation learning for cross-domain recommendation. 33rd ACM Web Conference, WWW 2024, Singapore, 13 May 2024. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3589334.3645337

Prompt-enhanced federated content representation learning for cross-domain recommendation

2024

Conference Publication

Unraveling the ‘Anomaly’ in time series anomaly detection: a self-supervised tri-domain solution

Sun, 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

Unraveling the ‘Anomaly’ in time series anomaly detection: a self-supervised tri-domain solution

2024

Conference Publication

Defense against model extraction attacks on recommender systems

Zhang, Sixiao, Yin, Hongzhi, Chen, Hongxu and Long, Cheng (2024). Defense against model extraction attacks on 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: 10.1145/3616855.3635751

Defense against model extraction attacks on recommender systems

2024

Conference Publication

Budgeted embedding table for recommender systems

Qu, 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

Budgeted embedding table for recommender systems

2024

Conference Publication

Motif-based prompt learning for universal cross-domain recommendation

Hao, Bowen, Yang, Chaoqun, Guo, Lei, Yu, Junliang and Yin, Hongzhi (2024). Motif-based prompt learning for universal cross-domain recommendation. 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: 10.1145/3616855.3635754

Motif-based prompt learning for universal cross-domain recommendation