publications

2024

1. SURVEY

   A Survey of Machine Learning for Urban Decision Making: Applications in Planning, Transportation, and Healthcare

   Yu Zheng, Qianyue Hao, Jingwei Wang, Changzheng Gao, Jinwei Chen, Depeng Jin, and Yong Li

   ACM Comput. Surv., Nov 2024

   Just Accepted

   Bib HTML PDF

   @article{zheng2024ml4urban,
     author = {Zheng, Yu and Hao, Qianyue and Wang, Jingwei and Gao, Changzheng and Chen, Jinwei and Jin, Depeng and Li, Yong},
     title = {A Survey of Machine Learning for Urban Decision Making: Applications in Planning, Transportation, and Healthcare},
     year = {2024},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     url = {https://doi.org/10.1145/3695986},
     doi = {10.1145/3695986},
     issn = {0360-0300},
     note = {Just Accepted},
     journal = {ACM Comput. Surv.},
     month = nov,
     keywords = {machine learning, urban planning, optimization, decision making}
   }

2. SIGSPATIAL

   Large-scale Urban Facility Location Selection with Knowledge-informed Reinforcement Learning

   Hongyuan Su*, Yu Zheng*, Jingtao Ding, Depeng Jin, and Yong Li

   In Proceedings of the 32nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Nov 2024

   arXiv Bib HTML PDF Code

   @inproceedings{su2024large,
     author = {Su*, Hongyuan and Zheng*, Yu and Ding, Jingtao and Jin, Depeng and Li, Yong},
     title = {Large-scale Urban Facility Location Selection with Knowledge-informed Reinforcement Learning},
     year = {2024},
     publisher = {Association for Computing Machinery},
     address = {Atlanta, GA, USA},
     url = {https://doi.org/10.1145/3678717.3691254},
     doi = {10.1145/3678717.3691254},
     booktitle = {Proceedings of the 32nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems},
     numpages = {4},
     keywords = {facility location problem, reinforcement learning, large-scale optimization},
     location = {Atlanta, GA, USA},
     series = {SIGSPATIAL '24}
   }

3. WWW

   Rumor Mitigation in Social Media Platforms with Deep Reinforcement Learning

   Hongyuan Su, Yu Zheng, Jingtao Ding, Depeng Jin, and Yong Li

   In Companion Proceedings of the ACM Web Conference 2024, Nov 2024

   arXiv Bib HTML PDF Code

   @inproceedings{su2024rumor,
     title = {Rumor Mitigation in Social Media Platforms with Deep Reinforcement Learning},
     author = {Su, Hongyuan and Zheng, Yu and Ding, Jingtao and Jin, Depeng and Li, Yong},
     year = {2024},
     isbn = {9798400701726},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     url = {https://doi.org/10.1145/3589335.3651556},
     doi = {10.1145/3589335.3651556},
     booktitle = {Companion Proceedings of the ACM Web Conference 2024},
     pages = {814–817},
     numpages = {4},
     keywords = {reinforcement learning, rumor mitigation, social platforms},
     location = {Singapore, Singapore},
     series = {WWW '24},
   }

4. WWW

   MetroGNN: Metro Network Expansion with Reinforcement Learning

   Hongyuan Su, Yu Zheng, Jingtao Ding, Depeng Jin, and Yong Li

   In Companion Proceedings of the ACM Web Conference 2024, Nov 2024

   arXiv Bib HTML PDF Code

   @inproceedings{su2024metrognn,
     title = {MetroGNN: Metro Network Expansion with Reinforcement Learning},
     author = {Su, Hongyuan and Zheng, Yu and Ding, Jingtao and Jin, Depeng and Li, Yong},
     isbn = {9798400701726},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     url = {https://doi.org/10.1145/3589335.3651536},
     year = {2024},
     doi = {10.1145/3589335.3651536},
     booktitle = {Companion Proceedings of the ACM Web Conference 2024},
     pages = {650–653},
     numpages = {4},
     keywords = {graph neural networks, metro network, reinforcement learning},
     location = {Singapore, Singapore},
     series = {WWW '24},
   }

5. WSDM

   Mixed Attention Network for Cross-domain Sequential Recommendation

   Guanyu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li, and Meng Wang

   In Proceedings of the 17th ACM International Conference on Web Search and Data Mining, Nov 2024

   arXiv Bib HTML PDF Code

   @inproceedings{lin2024mixed,
     author = {Lin, Guanyu and Gao, Chen and Zheng, Yu and Chang, Jianxin and Niu, Yanan and Song, Yang and Gai, Kun and Li, Zhiheng and Jin, Depeng and Li, Yong and Wang, Meng},
     title = {Mixed Attention Network for Cross-domain Sequential Recommendation},
     year = {2024},
     isbn = {9798400703713},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     url = {https://doi.org/10.1145/3616855.3635801},
     doi = {10.1145/3616855.3635801},
     booktitle = {Proceedings of the 17th ACM International Conference on Web Search and Data Mining},
     pages = {405–413},
     numpages = {9},
     keywords = {keywords{cross-domain sequential recommendation, mixed attention network, recommender systems}},
     location = {<conf-loc>, <city>Merida</city>, <country>Mexico</country>, </conf-loc>},
     series = {WSDM '24}
   }

6. WSDM

   Inverse Learning with Extremely Sparse Feedback for Recommendation

   Guanyu Lin, Chen Gao, Yu Zheng, Yinfeng Li, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Zhiheng Li, Depeng Jin, and Yong Li

   In Proceedings of the 17th ACM International Conference on Web Search and Data Mining, Nov 2024

   arXiv Bib HTML PDF Code

   @inproceedings{lin2024inverse,
     author = {Lin, Guanyu and Gao, Chen and Zheng, Yu and Li, Yinfeng and Chang, Jianxin and Niu, Yanan and Song, Yang and Gai, Kun and Li, Zhiheng and Jin, Depeng and Li, Yong},
     title = {Inverse Learning with Extremely Sparse Feedback for Recommendation},
     year = {2024},
     isbn = {9798400703713},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     url = {https://doi.org/10.1145/3616855.3635797},
     doi = {10.1145/3616855.3635797},
     booktitle = {Proceedings of the 17th ACM International Conference on Web Search and Data Mining},
     pages = {396–404},
     numpages = {9},
     keywords = {de-noising, meta learning, recommendation, sparse feedback},
     location = {<conf-loc>, <city>Merida</city>, <country>Mexico</country>, </conf-loc>},
     series = {WSDM '24}
   }

7. SURVEY

   Causal Inference in Recommender Systems: A Survey and Future Directions

   Chen Gao, Yu Zheng, Wenjie Wang, Fuli Feng, Xiangnan He, and Yong Li

   ACM Trans. Inf. Syst., Feb 2024

   arXiv Bib HTML PDF Code

   @article{gao2024causal,
     author = {Gao, Chen and Zheng, Yu and Wang, Wenjie and Feng, Fuli and He, Xiangnan and Li, Yong},
     title = {Causal Inference in Recommender Systems: A Survey and Future Directions},
     year = {2024},
     issue_date = {July 2024},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     volume = {42},
     number = {4},
     issn = {1046-8188},
     url = {https://doi.org/10.1145/3639048},
     doi = {10.1145/3639048},
     journal = {ACM Trans. Inf. Syst.},
     month = feb,
     articleno = {88},
     numpages = {32},
     keywords = {Recommender systems; causal inference; information retrieval}
   }

2023

1. NatComputSci

   Spatial planning of urban communities via deep reinforcement learning

   Yu Zheng, Yuming Lin, Liang Zhao, Tinghai Wu, Depeng Jin, and Yong Li

   Nature Computational Science, Feb 2023

   Bib HTML PDF Supp Code Poster

   @article{zheng2023spatial,
     title = {Spatial planning of urban communities via deep reinforcement learning},
     author = {Zheng, Yu and Lin, Yuming and Zhao, Liang and Wu, Tinghai and Jin, Depeng and Li, Yong},
     journal = {Nature Computational Science},
     pages = {1--15},
     year = {2023},
     publisher = {Nature Publishing Group US New York},
     doi = {10.1038/s43588-023-00503-5},
     url = {https://www.nature.com/articles/s43588-023-00503-5},
   }

2. KDD

   Road Planning for Slums via Deep Reinforcement Learning

   Yu Zheng*, Hongyuan Su*, Jingtao Ding, Depeng Jin, and Yong Li

   In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Feb 2023

   arXiv Bib HTML PDF Code Poster

   @inproceedings{zheng2023road,
     author = {Zheng*, Yu and Su*, Hongyuan and Ding, Jingtao and Jin, Depeng and Li, Yong},
     title = {Road Planning for Slums via Deep Reinforcement Learning},
     year = {2023},
     isbn = {9798400701030},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     url = {https://doi.org/10.1145/3580305.3599901},
     doi = {10.1145/3580305.3599901},
     booktitle = {Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
     pages = {5695–5706},
     numpages = {12},
     keywords = {slum upgrading, reinforcement learning, road planning},
     location = {Long Beach, CA, USA},
     series = {KDD '23},
   }

3. SURVEY

   A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions

   Chen Gao*, Yu Zheng*, Nian Li, Yinfeng Li, Yingrong Qin, Jinghua Piao, Yuhan Quan, Jianxin Chang, Depeng Jin, Xiangnan He, and Yong Li

   ACM Trans. Recomm. Syst., Mar 2023

   arXiv Bib HTML PDF Code

   @article{gao2023graph,
     author = {Gao*, Chen and Zheng*, Yu and Li, Nian and Li, Yinfeng and Qin, Yingrong and Piao, Jinghua and Quan, Yuhan and Chang, Jianxin and Jin, Depeng and He, Xiangnan and Li, Yong},
     title = {A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions},
     year = {2023},
     issue_date = {March 2023},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     volume = {1},
     number = {1},
     url = {https://doi.org/10.1145/3568022},
     doi = {10.1145/3568022},
     journal = {ACM Trans. Recomm. Syst.},
     month = mar,
     articleno = {3},
     numpages = {51},
     keywords = {graph representation learning, information retrieval, Recommender systems, graph neural networks}
   }

4. WWW

   Dual-interest Factorization-heads Attention for Sequential Recommendation

   Guanyu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang Song, Zhiheng Li, Depeng Jin, and Yong Li

   In Proceedings of the ACM Web Conference 2023, Mar 2023

   arXiv Bib HTML PDF Code

   @inproceedings{lin2023dual,
     author = {Lin, Guanyu and Gao, Chen and Zheng, Yu and Chang, Jianxin and Niu, Yanan and Song, Yang and Li, Zhiheng and Jin, Depeng and Li, Yong},
     title = {Dual-interest Factorization-heads Attention for Sequential Recommendation},
     year = {2023},
     isbn = {9781450394161},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     url = {https://doi.org/10.1145/3543507.3583278},
     doi = {10.1145/3543507.3583278},
     booktitle = {Proceedings of the ACM Web Conference 2023},
     pages = {917–927},
     numpages = {11},
     keywords = {Contrastive Learning, Sequential recommendation, User feedback},
     location = {<conf-loc>, <city>Austin</city>, <state>TX</state>, <country>USA</country>, </conf-loc>},
     series = {WWW '23}
   }

5. TKDE

   Incorporating Price into Recommendation With Graph Convolutional Networks

   Yu Zheng, Chen Gao, Xiangnan He, Depeng Jin, and Yong Li

   IEEE Transactions on Knowledge and Data Engineering, Mar 2023

   Bib HTML Code

   @article{zheng2021incorporating,
     author = {Zheng, Yu and Gao, Chen and He, Xiangnan and Jin, Depeng and Li, Yong},
     title = {Incorporating Price into Recommendation With Graph Convolutional Networks},
     journal = {IEEE Transactions on Knowledge and Data Engineering},
     year = {2023},
     volume = {35},
     number = {2},
     issn = {1558-2191},
     pages = {1609-1623},
     doi = {10.1109/TKDE.2021.3091160},
     url = {https://doi.org/10.1109/TKDE.2021.3091160},
   }

2022

1. MM

   DVR: Micro-Video Recommendation Optimizing Watch-Time-Gain under Duration Bias

   Yu Zheng, Chen Gao, Jingtao Ding, Lingling Yi, Depeng Jin, Yong Li, and Meng Wang

   In Proceedings of the 30th ACM International Conference on Multimedia, Mar 2022

   arXiv Bib HTML PDF Code Poster

   @inproceedings{zheng2022dvr,
     author = {Zheng, Yu and Gao, Chen and Ding, Jingtao and Yi, Lingling and Jin, Depeng and Li, Yong and Wang, Meng},
     title = {DVR: Micro-Video Recommendation Optimizing Watch-Time-Gain under Duration Bias},
     year = {2022},
     isbn = {9781450392037},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     url = {https://doi.org/10.1145/3503161.3548428},
     doi = {10.1145/3503161.3548428},
     booktitle = {Proceedings of the 30th ACM International Conference on Multimedia},
     pages = {334–345},
     numpages = {12},
     keywords = {micro-video, recommendation, duration bias},
     location = {Lisboa, Portugal},
     series = {MM '22}
   }

2. WWW

   Disentangling Long and Short-Term Interests for Recommendation

   Yu Zheng, Chen Gao, Jianxin Chang, Yanan Niu, Yang Song, Depeng Jin, and Yong Li

   In Proceedings of the ACM Web Conference 2022, Mar 2022

   arXiv Bib HTML PDF Code Poster

   @inproceedings{zheng2022disentangling,
     author = {Zheng, Yu and Gao, Chen and Chang, Jianxin and Niu, Yanan and Song, Yang and Jin, Depeng and Li, Yong},
     title = {Disentangling Long and Short-Term Interests for Recommendation},
     year = {2022},
     isbn = {9781450390965},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     url = {https://doi.org/10.1145/3485447.3512098},
     doi = {10.1145/3485447.3512098},
     booktitle = {Proceedings of the ACM Web Conference 2022},
     pages = {2256–2267},
     numpages = {12},
     keywords = {Self-supervised Learning, Disentanglement Learning, Recommendation, Long and Short-Term Interests},
     location = {Virtual Event, Lyon, France},
     series = {WWW '22}
   }

3. SIGIR

   Dual Contrastive Network for Sequential Recommendation

   Guanyu Lin, Chen Gao, Yinfeng Li, Yu Zheng, Zhiheng Li, Depeng Jin, and Yong Li

   In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Mar 2022

   Bib HTML PDF

   @inproceedings{lin2022dcn,
     author = {Lin, Guanyu and Gao, Chen and Li, Yinfeng and Zheng, Yu and Li, Zhiheng and Jin, Depeng and Li, Yong},
     title = {Dual Contrastive Network for Sequential Recommendation},
     year = {2022},
     isbn = {9781450387323},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     url = {https://doi.org/10.1145/3477495.3531918},
     doi = {10.1145/3477495.3531918},
     booktitle = {Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval},
     pages = {2686–2691},
     numpages = {6},
     keywords = {sequential recommendation, self-supervised learning, contrastive learning},
     location = {Madrid, Spain},
     series = {SIGIR '22}
   }

2021

1. WWW

   Disentangling User Interest and Conformity for Recommendation with Causal Embedding

   Yu Zheng, Chen Gao, Xiang Li, Xiangnan He, Yong Li, and Depeng Jin

   In Proceedings of the Web Conference 2021, Mar 2021

   arXiv Bib HTML PDF Code

   @inproceedings{zheng2021disentangling,
     author = {Zheng, Yu and Gao, Chen and Li, Xiang and He, Xiangnan and Li, Yong and Jin, Depeng},
     title = {Disentangling User Interest and Conformity for Recommendation with Causal Embedding},
     year = {2021},
     isbn = {9781450383127},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     url = {https://doi.org/10.1145/3442381.3449788},
     doi = {10.1145/3442381.3449788},
     booktitle = {Proceedings of the Web Conference 2021},
     pages = {2980–2991},
     numpages = {12},
     keywords = {Recommender systems, causal embedding, popularity bias},
     location = {Ljubljana, Slovenia},
     series = {WWW '21},
   }

2. WWW

   DGCN: Diversified Recommendation with Graph Convolutional Networks

   Yu Zheng, Chen Gao, Liang Chen, Depeng Jin, and Yong Li

   In Proceedings of the Web Conference 2021, Mar 2021

   arXiv Bib HTML PDF Code

   @inproceedings{zheng2021dgcn,
     author = {Zheng, Yu and Gao, Chen and Chen, Liang and Jin, Depeng and Li, Yong},
     title = {DGCN: Diversified Recommendation with Graph Convolutional Networks},
     year = {2021},
     isbn = {9781450383127},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     url = {https://doi.org/10.1145/3442381.3449835},
     doi = {10.1145/3442381.3449835},
     booktitle = {Proceedings of the Web Conference 2021},
     pages = {401–412},
     numpages = {12},
     keywords = {diversification, graph convolutional networks, Recommender systems},
     location = {Ljubljana, Slovenia},
     series = {WWW '21}
   }

3. SIGIR

   Sequential Recommendation with Graph Neural Networks

   Jianxin Chang, Chen Gao, Yu Zheng, Yiqun Hui, Yanan Niu, Yang Song, Depeng Jin, and Yong Li

   In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Mar 2021

   arXiv Bib HTML PDF Code

   @inproceedings{chang2021surge,
     author = {Chang, Jianxin and Gao, Chen and Zheng, Yu and Hui, Yiqun and Niu, Yanan and Song, Yang and Jin, Depeng and Li, Yong},
     title = {Sequential Recommendation with Graph Neural Networks},
     year = {2021},
     isbn = {9781450380379},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     url = {https://doi.org/10.1145/3404835.3462968},
     doi = {10.1145/3404835.3462968},
     booktitle = {Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval},
     pages = {378–387},
     numpages = {10},
     keywords = {graph neural networks, sequential recommendation, dynamic user preferences},
     location = {Virtual Event, Canada},
     series = {SIGIR '21}
   }

4. CSCW

   Bringing Friends into the Loop of Recommender Systems: An Exploratory Study

   Jinghua Piao, Guozhen Zhang, Fengli Xu, Zhilong Chen, Yu Zheng, Chen Gao, and Yong Li

   Proc. ACM Hum.-Comput. Interact., Oct 2021

   Bib HTML PDF

   @article{piao2021cscw,
     author = {Piao, Jinghua and Zhang, Guozhen and Xu, Fengli and Chen, Zhilong and Zheng, Yu and Gao, Chen and Li, Yong},
     title = {Bringing Friends into the Loop of Recommender Systems: An Exploratory Study},
     year = {2021},
     issue_date = {October 2021},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     volume = {5},
     number = {CSCW2},
     url = {https://doi.org/10.1145/3479583},
     doi = {10.1145/3479583},
     journal = {Proc. ACM Hum.-Comput. Interact.},
     month = oct,
     articleno = {439},
     numpages = {26},
     keywords = {human-in-the-loop, personalized recommender system, social e-commerce, friends' recommendations, friend in the loop}
   }

2020

1. ICDE

   Price-aware Recommendation with Graph Convolutional Networks

   Yu Zheng, Chen Gao, Xiangnan He, Yong Li, and Depeng Jin

   In 2020 IEEE 36th International Conference on Data Engineering (ICDE), Oct 2020

   arXiv Bib HTML PDF Code

   @inproceedings{zheng2020price,
     author = {Zheng, Yu and Gao, Chen and He, Xiangnan and Li, Yong and Jin, Depeng},
     booktitle = {2020 IEEE 36th International Conference on Data Engineering (ICDE)},
     title = {Price-aware Recommendation with Graph Convolutional Networks},
     year = {2020},
     volume = {},
     number = {},
     pages = {133-144},
     doi = {10.1109/ICDE48307.2020.00019},
   }