Publications

Our Recent Tutorials and Surveys

• Yongxin Tong, Zimu Zhou, Yuxiang Zeng, Lei Chen, Cyrus Shahabi. "Spatial Crowdsourcing: A Survey", The VLDB Journal (VLDBJ), 29(1): 217-250, January 2020. [VLDB 2017 Tutorial Slides]
• Qiang Yang, Yang Liu, Tianjian Chen, Yongxin Tong. "Federated Machine Learning: Concept and Applications", ACM Transactions on Intelligent Systems and Technology (TIST), 10(2): No.12, February 2019.

Recent Selected Publications

[My DBLP Entry] [My Google Scholar Page] [Full Publication List]

• Yuxiang Wang, Yuxiang Zeng, Shuyuan Li, Yuanyuan Zhang, Zimu Zhou, Yongxin Tong. “Efficient and Private Federated Trajectory Matching”, to appear in IEEE Transactions on Knowledge and Data Engineering (TKDE 2024), .
• Shuyuan Li, Yuxiang Zeng, Yuxiang Wang, Yiman Zhong, Zimu Zhou, Yongxin Tong. “An Experimental Study on Federated Equi-Joins”, IEEE Transactions on Knowledge and Data Engineering (TKDE 2024), 36(9): 4443-4457, 2024.[Code and Data]
• Boyi Liu, Yiming Ma, Zimu Zhou, Yexuan Shi, Shuyuan Li, Yongxin Tong. “CASA: Clustered Federated Learning with Asynchronous Clients”, in Proceedings of the 30th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD 2024), Barcelona, Spain, August 25-29, 2024.[Code and Data]
• Linghua Yang, Wantong Chen, Xiaoxi He, Shuyue Wei, Yi Xu, Zimu Zhou, Yongxin Tong. “FedGTP: Exploiting Inter-Client Spatial Dependency in Federated Graph-based Traffic Prediction”, in Proceedings of the 30th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD 2024), Barcelona, Spain, August 25-29, 2024.[Code and Data]
• Jianyang Qin, Yan Jia, Yongxin Tong, Heyan Chai, Xuan Wang, Binxing Fang, Qing Liao. “MUSE-Net: Disentangling Multi-Periodicity for Traffic Flow Forecasting”, in Proceedings of the 40th International Conference on Data Engineering (ICDE 2024), Utrecht, Netherlands, May 13-17, 2024.
• Wei Yuan, Liang Qu, Lizhen Cui, Yongxin Tong, Xiaofang Zhou, Hongzhi Yin. “HeteFedRec: Federated Recommender Systems with Model Heterogeneity”, in Proceedings of the 40th International Conference on Data Engineering (ICDE 2024), Utrecht, Netherlands, May 13-17, 2024.
• Heyan Chai, Zeyu Liu, Yongxin Tong, Ziyi Yao, Binxing Fang, Qing Liao. “Towards Task-Conflicts Momentum-Calibrated Approach for Multi-task Learning”, in Proceedings of the 40th International Conference on Data Engineering (ICDE 2024), Utrecht, Netherlands, May 13-17, 2024.
• Dingyuan Shi, Yongxin Tong, Zimu Zhou, Ke Xu, Zheng Wang, Jieping Ye. “Graph-Constrained Diffusion for End-to-end Path Planning”, in Proceedings of the 12th International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024.[Code and Data]
• Yongxin Tong, Dingyuan Shi, Yi Xu, Weifeng Lv, Zhiwei Qin, Xiaocheng Tang. “Combinatorial Optimization Meets Reinforcement Learning: Effective Taxi Order Dispatching at Large-Scale”, IEEE Transactions on Knowledge and Data Engineering (TKDE 2023), 35(10): 9812-9823, 2023.
• Yexuan Shi, Yongxin Tong, Yuxiang Zeng, Zimu Zhou, Bolin Ding, Lei Chen. “Efficient Approximate Range Aggregation over Large-scale Spatial Data Federation”, IEEE Transactions on Knowledge and Data Engineering (TKDE 2023), 35(1): 418-430, 2023.
• Yuxiang Zeng, Yongxin Tong, Lei Chen. “LiteHST: A Tree Embedding based Method for Similarity Search”, in Proceedings of the 42nd ACM SIGMOD International Conference on Management of Data (SIGMOD 2023), Pages 1-26, Seattle, WA, USA, June 18-23.
• Wenhao Zhang, Zimu Zhou, Yansheng Wang, Yongxin Tong. “DM-PFL: Hitchhiking Generic Federated Learning for Efficient Shift-Robust Personalization”, in Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2023), Pages 3396-3408, CA, USA, August 6-10, 2023.
• Liyue Chen, Jiangyi Fang, Zhe Yu, Yongxin Tong, Shaosheng Cao, Leye Wang. “A Data-driven Region Generation Framework for Spatiotemporal Transportation Service Management”, in Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2023), Pages 3842-3854, CA, USA, August 6-10, 2023.
• Yansheng Wang, Yongxin Tong, Zimu Zhou, Ruisheng Zhang, Sinno Jialin Pan, Lixin Fan, Qiang Yang. “Distribution-Regularized Federated Learning on Non-IID Data”, in Proceedings of the 39th International Conference on Data Engineering (ICDE 2023), Pages 2113-2125, CA, USA, April 3-7, 2023.[Code and Data]
• Dingyuan Shi, Nan Zhou, Yongxin Tong, Zimu Zhou, Yi Xu, Ke Xu. “Collision-Aware Route Planning in Warehouses Made Efficient: A Strip-based Framework”, in Proceedings of the 39th International Conference on Data Engineering (ICDE 2023), Pages 869-881, CA, USA, April 3-7, 2023.
• Shuyue Wei, Yongxin Tong, Zimu Zhou, Qiaoyang Liu, Lulu Zhang, Yuxiang Zeng, Jieping Ye. “Towards Capacity-Aware Broker Matching: From Recommendation to Assignment”, in Proceedings of the 39th International Conference on Data Engineering (ICDE 2023), Pages 776-788, CA, USA, April 3-7, 2023.

• Yongxin Tong, Yuxiang Zeng, Zimu Zhou, Lei Chen, Ke Xu. "Unified Route Planning for Shared Mobility: An Insertion-based Framework", ACM Transactions on Database Systems (TODS 2022), 47(1): 2:1-2:48, 2022. [Code and Data]
• Yi Xu, Yongxin Tong, Yexuan Shi, Qian Tao, Ke Xu, Wei Li. "An Efficient Insertion Operator in Dynamic Ridesharing Services", IEEE Transactions on Knowledge and Data Engineering (TKDE 2022), 34(8): 3583-3596, 2022. [Slides] (One of the Best Paper Nominations in ICDE 2019)
• Hao Liu, Yongxin Tong, Jindong Han, Panpan Zhang, Xinjiang Lu, Hui Xiong. "Incorporating Multi-Source Urban Data for Personalized and Context-Aware Multi-Modal Transportation Recommendation", IEEE Transactions on Knowledge and Data Engineering (TKDE 2022), 34(2): 723-735, 2022.
• Yongxin Tong, Xuchen Pan, Yuxiang Zeng, Yexuan Shi, Chunbo Xue, Zimu Zhou, Xiaofei Zhang, Lei Chen, Yi Xu, Ke Xu, Weifeng Lv. "Hu-Fu: Efficient and Secure Spatial Queries over Data Federation", Proceedings of the VLDB Endowment (PVLDB 2022), 15(6): 1159-1172, 2022. [Code and Data]
• Xuchen Pan, Yongxin Tong, Chunbo Xue, Zimu Zhou, Junping Du, Yuxiang Zeng, Yexuan Shi, Xiaofei Zhang, Lei Chen, Yi Xu, Ke Xu, Weifeng Lv. "Hu-Fu: A Data Federation System for Secure Spatial Queries" (Demo paper), Proceedings of the VLDB Endowment (PVLDB 2022), 15(12): 3582-3585, 2022.
• Yansheng Wang, Yongxin Tong, Zimu Zhou, Ziyao Ren, Yi Xu, Guobin Wu, Weifeng Lv. "Fed-LTD: Towards Cross-Platform Ride Hailing via Federated Learning to Dispatch", in Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2022), Washington D.C., USA, August 14-18, 2022.
• Zhongnan Qu, Zimu Zhou, Yongxin Tong, Lothar Thiele. "Fed-LTD: Towards Cross-Platform Ride Hailing via Federated Learning to Dispatch", in Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2022), Washington D.C., USA, August 14-18, 2022.
• Yuxiang Zeng, Yongxin Tong, Lei Chen. "Faster and Better Solution to Embed Lp Metrics by Tree Metrics", in Proceedings of the 41st ACM SIGMOD International Conference on Management of Data (SIGMOD 2022), Philadelphia, PA, USA, June 12-17, 2022.
• Dingyuan Shi, Yongxin Tong, Zimu Zhou, Ke Xu, Wenzhe Tan, Hongbo Li. "Adaptive Task Planning for Large-Scale Robotized Warehouses", in Proceedings of the 38th International Conference on Data Engineering (ICDE 2022), Kuala Lumpur, Malaysia, May 9-12, 2022.
• Yongxin Tong, Yuxiang Zeng, Bolin Ding, Libin Wang, Lei Chen. "Two-Sided Online Micro-Task Assignment in Spatial Crowdsourcing", IEEE Transactions on Knowledge and Data Engineering (TKDE 2021), 33(5): 2295 - 2309, May 2021. [Code and Data]
• Dingyuan Shi, Yongxin Tong, Zimu Zhou, Bingchen Song, Weifeng Lv, Qiang Yang. "Learning to Assign: Towards Fair Task Assignment in Large-Scale Ride Hailing", in Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2021), Singapore, Singapore, August 14-18, 2021. [Slides]
• Yuxiang Zeng, Yongxin Tong, Lei Chen. "Last-Mile Delivery Made Practical: An Efficient Route Planning Framework with Theoretical Guarantees", in Proceedings of the 46th International Conference on Very Large Databases (VLDB 2020), Tokyo, Japan, August 31-September 4, 2020. [Slides] [Poster] [Code and Data]
• Yansheng Wang, Yongxin Tong, Dingyuan Shi. "Federated Latent Dirichlet Allocation: A Local Differential Privacy Based Framework", in Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI 2020), New York, USA, January 7-12, 2020. [Slides] [Poster]
• Yansheng Wang, Yongxin Tong, Cheng Long, Pan Xu, Ke Xu, Weifeng Lv. "Adaptive Dynamic Bipartite Graph Matching: A Reinforcement Learning Approach", in Proceedings of the 35h International Conference on Data Engineering (ICDE 2019), Macau, China, April 8-12, 2019. [Slides] [Poster]
• Yongxin Tong, Yuxiang Zeng, Zimu Zhou, Lei Chen, Jieping Ye, Ke Xu. "A Unified Approach to Route Planning for Shared Mobility", in Proceedings of the 44th International Conference on Very Large Databases (VLDB 2018), Rio de Janeiro, Brazil, August 27-31, 2018. [Slides] [Poster] [Code and Data]
• Yongxin Tong, Lei Chen, Zimu Zhou, H. V. Jagadish, Lidan Shou, Weifeng Lv. "SLADE: A Smart Large-Scale Task Decomposer in Crowdsourcing", IEEE Transactions on Knowledge and Data Engineering (TKDE 2018), 30(8): 1588 - 1601, August 2018.
• Yongxin Tong, Libin Wang, Zimu Zhou, Lei Chen, Bowen Du, Jieping Ye. "Dynamic Pricing in Spatial Crowdsourcing: A Matching-Based Approach", in Proceedings of the 37th ACM SIGMOD International Conference on Management of Data (SIGMOD 2018), Houston, TX, USA, June 10-15, 2018. [Slides] [Poster]
• Yongxin Tong, Libin Wang, Zimu Zhou, Bolin Ding, Lei Chen, Jieping Ye, Ke Xu. "Flexible Dynamic Task Assignment in Real-Time Spatial Data", in Proceedings of the 43rd International Conference on Very Large Databases (VLDB 2017), Munich, Germany, August 28-September 1, 2017. [Slides] [Poster] [Code and Data]
• Yongxin Tong, Yuqiang Chen, Zimu Zhou, Lei Chen, Jie Wang, Qiang Yang, Jieping Ye, Weifeng Lv. "The Simpler The Better: A Unified Approach to Predicting Original Taxi Demands on Large-Scale Online Platforms", in Proceedings of the 23rd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2017), Halifax, Nova Scotia, Canada, August 13-17, 2017. [Slides] [Poster] [Short Promotional Video]
• Yongxin Tong, Jieying She, Bolin Ding, Lei Chen, Tianyu Wo, Ke Xu. "Online Minimum Matching in Real-Time Spatial Data: Experiments and Analysis", in Proceedings of the 42nd International Conference on Very Large Databases (VLDB 2016), New Delhi, India, September 5-9, 2016. [Slides] [Poster]
• Yongxin Tong, Jieying She, Bolin Ding, Libin Wang, Lei Chen. "Online Mobile Micro-Task Allocation in Spatial Crowdsourcing", in Proceedings of the 32nd International Conference on Data Engineering (ICDE 2016), Helsinki, Finland, May 16-20, 2016. [Slides] [Poster] [Code and Data]