Publications

  • [CIKM] TrajFormer: Efficient Trajectory Classification with Transformers.

    In Proceedings of The 31st ACM International Conference on Information and Knowledge Management, 2022.

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  • [CIKM] Generative-Free Urban Flow Imputation.

    In Proceedings of The 31st ACM International Conference on Information and Knowledge Management, 2022.

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  • [KDD] Precision CityShield Against Hazardous Chemicals Threats via Location Mining and Self-Supervised Learning.

    In Proceedings of The 28th ACM SIGKDD international conference on Knowledge Discovery and Data Mining, 2022.

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  • [TKDE] Forecasting Fine-grained Urban Flow via Spatio-temporal Contrastive Self-Supervision.

    IEEE Transactions on Knowledge and Data Engineering, 2022.

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  • [DeepSpatial] EAST: An Enhanced Automated Machine Learning Library for Spatio-Temporal Forecasting.

    In The 3rd ACM SIGKDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems, 2022.

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  • [DASFAA] Multi-Memory enhanced Separation Network for Indoor Temperature Prediction.

    In Proceedings of DASFAA 2022 (DASFAA'22).

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  • [TKDE] Shortening passengers' travel time: A dynamic metro train scheduling approach using deep reinforcement learning.

    IEEE Transactions on Knowledge and Data Engineering, 2022.

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  • [TKDE] Fine-grained Urban Flow Inference with Incomplete Data.

    IEEE Transactions on Knowledge and Data Engineering, 2022.

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  • [TKDE] Cross-domain knowledge graph chiasmal embedding for multi-domain item-item recommendation.

    IEEE Transactions on Knowledge and Data Engineering, 2022.

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  • [InfSci] Fairness and accuracy in horizontal federated learning.

    Information Sciences, 2022.

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  • [TKDE] Urban flow pattern mining based on multi-source heterogeneous data fusion and knowledge graph embedding.

    IEEE Transactions on Knowledge and Data Engineering, 2021.

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  • [TKDE] TrajMesa: A Distributed NoSQL-Based Trajectory Data Management System.

    IEEE Transactions on Knowledge and Data Engineering, 2021.

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  • [TKDE] Gas-Theft Suspect Detection among Boiler Room Users: A Data-Driven Approach.

    IEEE Transactions on Knowledge and Data Engineering, 2021.

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  • [WWW] Fine-grained Urban Flow Prediction.

    In Proceedings of The Web Conference 2021 (WWW'21).

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  • [WWW] AutoSTG: Neural Architecture Search for Predictions of Spatio-Temporal Graph.

    In Proceedings of The Web Conference 2021 (WWW'21).

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  • [AAAI] Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network.

    In Proceedings of the 35th AAAI Conference.

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  • [TBD] Predicting Fine-Grained Air Quality Based on Deep Neural Networks.

    IEEE Transactions on Big Data, 2020.

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  • [IEEE IntSys] Federated Digital Gateway: Methodologies, Tools and Applications.

    IEEE Intelligent Systems, 2020.

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  • [CIKM] You Are How You Use: Catching Gas Theft Suspects among Diverse Restaurant Users.

    In Proceedings of The 29th ACM International Conference on Information and Knowledge Management.

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  • [TKDE] Predicting Citywide Crowd Flows in Irregular Regions Using Multi-View Graph Convolutional Networks.

    IEEE Transactions on Knowledge and Data Engineering, 2020.

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  • [ECML-PKDD] Revisiting Convolutional Neural Networks for Citywide Crowd Flow Analytics.

    In Proceedings of ECML-PKDD 2020.

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  • [KDD] AutoST: Efficient Neural Architecture Search for Spatio-Temporal Prediction.

    In Proceedings of The 26th ACM SIGKDD international conference on Knowledge Discovery and Data Mining, 2020.

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  • [TKDE] Spatio-Temporal Meta Learning for Urban Traffic Prediction.

    IEEE Transactions on Knowledge and Data Engineering, 2020.

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  • [TBD] Federated Forest.

    IEEE Transactions on Big Data, 2020.

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  • [InfFus] Predicting and ranking box office revenue of movies based on big data.

    Information Fusion, 2020.

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  • [InfFus] Urban flow prediction from spatiotemporal data using machine learning: A survey.

    Information Fusion, 2020.

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  • [UbiComp] CityGuard: Citywide Fire Risk Forecasting Using A Machine Learning Approach.

    In Proceedings of The 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing.

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  • [CIKM] Matrix Factorization for Spatio-Temporal Neural Networks with Applications to Urban Flow Prediction.

    In Proceedings of The 28th ACM International Conference on Information and Knowledge Management.

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  • [CIKM] CityTraffic: Modeling Citywide Traffic via Neural Memorization and Generalization Approach.

    In Proceedings of The 28th ACM International Conference on Information and Knowledge Management.

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  • [KDD] UrbanFM: Inferring Fine-Grained Urban Flows.

    In Proceedings of The 25th ACM SIGKDD international conference on Knowledge Discovery and Data Mining.

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  • [KDD] Urban Traffic Prediction from Spatio-Temporal Data using Deep Meta Learning.

    In Proceedings of The 25th ACM SIGKDD international conference on Knowledge Discovery and Data Mining.

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  • [ACL] DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction.

    In Proceedings of The 57th Annual Meeting of the Association for Computational Linguistics.

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  • [TKDE] Flow Prediction in Spatio-Temporal Networks Based on Multitask Deep Learning.

    IEEE Transactions on Knowledge and Data Engineering, 2020.

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  • [CIKM] DeepCrime: Attentive Hierarchical Recurrent Networks for Crime Prediction.

    In Proceedings of The 27th ACM International Conference on Information and Knowledge Management.

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  • [KDD] Deep Distributed Fusion Network for Air Quality Prediction.

    In Proceedings of The 24th ACM SIGKDD international conference on Knowledge Discovery and Data Mining.

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  • [IJCAI] GeoMAN: Multi-level Attention Networks for Geo-sensory Time Series Prediction.

    In Proceedings of The 27th International Joint Conference on Artificial Intelligence.

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  • [AI] Predicting Citywide Crowd Flows Using Deep Spatio-Temporal Residual Networks.

    Artificial Intelligence, 2018.

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  • [AAAI] When Will You Arrive Estimating Travel Time Based on Deep Neural Networks.

    In Proceedings of Thirty-Second AAAI Conference on Artificial Intelligence.

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  • [AAAI] Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction.

    In Proceedings of The 31st AAAI Conference on Artificial Intelligence.

    PDF Code Dataset Project Project Most influential AAAI papers

  • [ACM SIGSPATIAL] DNN-Based Prediction Model for Spatial-Temporal Data.

    In Proceedings of The 24th ACM International Conference on Advances in Geographical Information Systems.

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  • [InfSci] Efficient parallel boolean matrix based algorithms for computing composite rough set approximations.

    Information Sciences, 2016.

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  • [TKDE] A Parallel Matrix-based Method for Computing Approximations in Incomplete Information Systems.

    IEEE Transactions on Knowledge and Data Engineering, 2015.

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  • [KDD] Supervised Deep Learning with Auxiliary Networks.

    In Proceedings of The 20th ACM SIGKDD international conference on Knowledge Discovery and Data Mining, 2014.

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  • [InfSci] Composite rough sets for dynamic data mining.

    Information Sciences, 2014.

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