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2025

Conference Publication

Progressive Generalization Risk Reduction for Data-Efficient Causal Effect Estimation

Wen, Hechuan, Chen, Tong, Ye, Guanhua, Chai, Li Kheng, Sadiq, Shazia and Yin, Hongzhi (2025). Progressive Generalization Risk Reduction for Data-Efficient Causal Effect Estimation. KDD '25: The 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Toronto, Canada, 3 - 7 August 2025. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3690624.3709305

Progressive Generalization Risk Reduction for Data-Efficient Causal Effect Estimation

2025

Conference Publication

BiasNavi: LLM-Empowered Data Bias Management

Yu, Junliang, Huynh, Jay Thai Duong, Fan, Shaoyang, Demartini, Gianluca, Chen, Tong, Yin, Hongzhi and Sadiq, Shazia (2025). BiasNavi: LLM-Empowered Data Bias Management. New York, NY, USA: ACM. doi: 10.1145/3701716.3715169

BiasNavi: LLM-Empowered Data Bias Management

2025

Conference Publication

Graph Condensation: Foundations, Methods and Prospects

Yin, Hongzhi, Gao, Xinyi, Yu, Junliang, Qiu, Ruihong, Chen, Tong, Nguyen, Quoc Viet Hung and Huang, Zi (2025). Graph Condensation: Foundations, Methods and Prospects. New York, NY, USA: ACM. doi: 10.1145/3701716.3715862

Graph Condensation: Foundations, Methods and Prospects

2025

Conference Publication

Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition

Gao, Xinyi, Ye, Guanhua, Chen, Tong, Zhang, Wentao, Yu, Junliang and Yin, Hongzhi (2025). Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition. WWW '25: The ACM Web Conference 2025, Sydney, NSW Australia, 28 April - 2 May 2025. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3696410.3714916

Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition

2025

Conference Publication

On-device Content-based Recommendation with Single-shot Embedding Pruning: A Cooperative Game Perspective

Tran, Hung Vinh, Chen, Tong, Ye, Guanhua, Nguyen, Quoc Viet Hung, Zheng, Kai and Yin, Hongzhi (2025). On-device Content-based Recommendation with Single-shot Embedding Pruning: A Cooperative Game Perspective. WWW '25: The ACM Web Conference 2025, Sydney, NSW Australia, 28 April - 2 May 2025. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3696410.3714921

On-device Content-based Recommendation with Single-shot Embedding Pruning: A Cooperative Game Perspective

2025

Conference Publication

Epidemiology-informed Network for Robust Rumor Detection

Jiang, Wei, Chen, Tong, Gao, Xinyi, Zhang, Wentao, Cui, Lizhen and Yin, Hongzhi (2025). Epidemiology-informed Network for Robust Rumor Detection. WWW '25: The ACM Web Conference 2025, Sydney, NSW Australia, 28 April - 2 May 2025. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3696410.3714610

Epidemiology-informed Network for Robust Rumor Detection

2025

Conference Publication

Towards Secure and Robust Recommender Systems: A Data-Centric Perspective

Wang, Zongwei, Yu, Junliang, Chen, Tong, Yin, Hongzhi, Sadiq, Shazia and Gao, Min (2025). Towards Secure and Robust Recommender Systems: A Data-Centric Perspective. 18th International Conference on Web Search and Data Mining-WSDM, Hannover Germany, Mar 10-14, 2025. New York, NY, USA: ACM. doi: 10.1145/3701551.3703484

Towards Secure and Robust Recommender Systems: A Data-Centric Perspective

2024

Conference Publication

Physics-guided active sample reweighting for urban flow prediction

Jiang, 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

Physics-guided active sample reweighting for urban flow prediction

2024

Conference Publication

Scalable dynamic embedding size search for streaming recommendation

Qu, 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

Scalable dynamic embedding size search for streaming recommendation

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

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

Fairness without sensitive attributes via knowledge sharing

Ni, Hongliang, Han, Lei, Chen, Tong, Sadiq, Shazia and Demartini, Gianluca (2024). Fairness without sensitive attributes via knowledge sharing. 2024 ACM Conference on Fairness, Accountability, and Transparency, Rio de Janeiro, Brazil, 3-6 June 2024. New York, NY, United States: ACM. doi: 10.1145/3630106.3659014

Fairness without sensitive attributes via knowledge sharing

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

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

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

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