Wentao Zhang

Wentao Zhang

北京大学 助理教授/研究员/博导

Publications

* indicates equal contribution, # indicates corresponding author

2024

  1. NC-ALG: Graph-based Active Learning under Noisy Crowd. [To appear]
    Wentao Zhang, Yexin Wang, Zhenbang You, Yang Li, Gang Cao, Zhi Yang, Bin Cui.
    ICDE 2024, CCF-A.

  2. Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation. [To appear]
    Xinyi Gao, Wentao Zhang#, Junliang Yu, Yingxia Shao, Quoc Viet Hung Nguyen, Bin Cui, Hongzhi Yin #.
    ICDE 2024, CCF-A.

  3. Graph Condensation for Inductive Node Representation Learning. [To appear]
    Xinyi Gao, Tong Chen, Yiling Zang, Wentao Zhang, Quoc Viet Hung Nguyen, Kai Zheng, Hongzhi Yin.
    ICDE 2024, CCF-A.

  4. AdaFGL: A New Paradigm for Federated Node Classification with Topology Heterogeneity. [To appear]
    Xunkai Li, Zhenyu Wu, Wentao Zhang, Henan Sun, Ronghua Li, Gouren Wang.
    ICDE 2024, CCF-A.

  5. Towards Effective and General Graph Unlearning via Mutual Evolution. [To appear]
    Xunkai Li, Yulin Zhao, Zhengyu Wu, Wentao Zhang, Ronghua Li, Gouren Wang.
    AAAI 2024, CCF-A.

2023

  1. Improving Diffusion-Based Image Synthesis with Context Prediction. [To appear]
    Ling Yang, Jingwei Liu, Shenda Hong, Zhilong Zhang, Zhilin Huang, Zheming Cai, Wentao Zhang#, Bin Cui#.
    NeurIPS 2023, CCF-A.

  2. Diffusion Models: A Comprehensive Survey of Methods. [To appear]
    Ling Yang, Zhilong Zhang, …, Wentao Zhang#, Bin Cui#, Ming-Hsuan Yang#.
    ACM Computing Survey.
    CSUR 2023, CCF-A.

  3. FedGTA: Topology-aware Averaging for Federated Graph Learning. [To appear]
    Xunkai Li, Zhenyu Wu, Wentao Zhang, Yinlin Zhu, Ronghua Li, Guoren Wang.
    International Conference on Very Large Data Bases.
    VLDB 2023, CCF-A.

  4. Rover: An online Spark SQL tuning service via generalized transfer learning. [To appear]
    Yu Shen, Xinyuyang Ren, Yupeng Lu, Huaijun Jiang, Di Peng, Huanyong Xu, Yang Li, Wentao Zhang#, Bin Cui.
    SIGKDD Conference on Knowledge Discovery and Data Mining.
    SIGKDD 2023, CCF-A.

  5. Towards General and Efficient Online Tuning for Spark. [To appear]
    Yang Li, Huanjun Jiang, …, Wentao Zhang, Ce Zhang, Peng Chen, Bin Cui.
    International Conference on Very Large Data Bases.
    VLDB 2023, CCF-A.

  6. Scapin : Scalable Graph Perturbation by Augmented Influence Maximization. [To appear]
    Yexin Wang, Zhi Yang, Junqi Liu, Wentao Zhang, Bin Cui.
    ACM SIGMOD International Conference on Management of Data.
    SIGMOD 2023, CCF-A.

  7. Individual and Structural Graph Information Bottlenecks for Out-of-Distribution Generalization. [To appear]
    Ling Yang, Jiayi Zheng, Heyuan Wang, Zhongyi Liu, Zhilin Huang, Shenda Hong, Wentao Zhang#, Bin Cui.
    IEEE Transactions on Knowledge and Data Engineering.
    TKDE 2023, CCF-A.

  8. ProxyBO: Accelerating Neural Architecture Search via Bayesian Optimization with Zero-cost Proxies. [Paper]
    Yu Shen, Yang Li, Jian Zheng, Peng Yao, Jixiang Li, Sen Yang, Ji Liu, Wentao Zhang#, Bin Cui.
    Thirty-Seventh AAAI Conference on Artificial Intelligence.
    AAAI 2023, CCF-A.

  9. Fairness-aware Maximal Biclique Enumeration on Bipartite Graphs. [Paper]
    Ziqi Yin, Qi Zhang, Wentao Zhang, Ronghua Li, Guoren Wang
    IEEE International Conference on Data Engineering.
    ICDE 2023, CCF-A.

  10. Semantic-aware Node Synthesis for Imbalanced Heterogeneous Information Networks. [To appear]
    Xinyi Gao, Wentao Zhang, Tong Chen, Junliang Yu, Quoc Viet Hung Nguyen and Hongzhi Yin
    ACM International Conference on Information and Knowledge Management.
    CIKM 2023, CCF-B.

  11. Graph-Enforced Neural Network for Attributed Graph Clustering. [To appear]
    Zeang Sheng, Wentao Zhang#, Yang Li, Wen Ouyang, Yangyu Tao, Zhi Yang and Bin Cui
    The 7th APWeb-WAIM International Joint Conference on Web and Big Data.
    APWeb-WAIM2023, CCF-C, 🏆 Best Paper Runner Up Award (among 260 submmisions).

2022

  1. NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning. [Paper][Code]
    Wentao Zhang, Zeang Sheng, Mingyu Yang, Yang Li, Yu Shen, Zhi Yang, Bin Cui.
    The 39th International Conference on Machine Learning.
    ICML 2022, CCF-A.

  2. Deep and Flexible Graph Neural Architecture Search. [Paper][Code]
    Wentao Zhang, Yu Shen, Zheyu Lin, Yang Li, Zhi Yang, Bin Cui.
    The 39th International Conference on Machine Learning.
    ICML 2022, CCF-A.

  3. Model Degradation Hinders Deep Graph Neural Networks. [Paper][Code]
    Wentao Zhang, Zeang Sheng, Yuezihan Jiang, Yikuan Xia, Jun Gao, Zhi Yang, Bin Cui.
    SIGKDD Conference on Knowledge Discovery and Data Mining.
    SIGKDD 2022, CCF-A.

  4. Graph Attention Multi-Layer Perceptron. [Paper][Code]
    Wentao Zhang, Ziqi Yin, Zeang Sheng, Wen Ouyang, Xiaosen Li, Yangyu Tao, Zhi Yang, Bin Cui.
    SIGKDD Conference on Knowledge Discovery and Data Mining.
    SIGKDD 2022, CCF-A.

  5. PaSca: a Graph Neural Architecture Search System under the Scalable Paradigm. [Paper][Code] [Doc]
    Wentao Zhang, Yu Shen, Zheyu Lin, Yang Li, Xiaosen Li, Wen Ouyang,Yangyu Tao, Zhi Yang, Bin Cui.
    The Web Conference.
    WWW 2022 (System Track), CCF-A, 🏆 Best Student Paper Award (among 1822 submmisions).

  6. Information Gain Propagation: a New Way to Graph Active Learning with Soft Labels . [Paper][Code]
    Wentao Zhang, Yexin Wang, Zhenbang You, …, Zhi Yang, Bin Cui.
    International Conference on Learning Representations.
    ICLR 2022.

  7. Graph Neural Networks in Recommender Systems: A Survey [Paper][Code]
    Shiwen Wu, Fei Sun, Wentao Zhang#, Xu Xie, Bin Cui.
    ACM Computing Surveys.
    CSUR 2022, CCF-A.

  8. P2CG: A Privacy Preserving Collaborative Graph Neural Network Training Framework.* [Paper]
    Xupeng Miao*, Wentao Zhang*, …, Lei Chen, Yangyu Tao, Gang Cao, Bin Cui.
    The International Journal on Very Large Data Bases.
    VLDBJ 2022, CCF-A.

  9. DivBO: Diversity-aware CASH for Ensemble Learning [Paper]
    Yu Shen, Yupeng Lu, Yang Li, Yaofeng Tu, Wentao Zhang, Bin CUI.
    NeurIPS 2022, CCF-A.

  10. TransBO: Hyperparameter Optimization via Two-Phase Transfer Learning. [Paper]
    Yang Li, Yu Shen, Huaijun Jiang, Wentao Zhang, Zhi Yang, Ce Zhang, Bin Cui.
    SIGKDD Conference on Knowledge Discovery and Data Mining.
    SIGKDD 2022, CCF-A.

  11. Transfer Learning based Search Space Design for Hyperparameter Tuning. [Paper]
    Yang Li, Yu Shen, Huaijun Jiang, Tianyi Bai, Wentao Zhang, Ce Zhang, Bin Cui.
    SIGKDD Conference on Knowledge Discovery and Data Mining.
    SIGKDD 2022, CCF-A.

  12. Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale. [Paper][Code]
    Yang Li, Yu Shen, Huaijun Jiang,Wentao Zhang, Jixiang Li, Ji Liu, Ce Zhang, Bin Cui.
    International Conference on Very Large Data Bases.
    VLDB 2022, CCF-A.

  13. Zoomer: Improving and Accelerating Recommendation on Web-Scale Graphs via Regions of Interests. [Paper][Code]
    Yuezihan Jiang, Yu Cheng, Hanyu Zhao, Wentao Zhang, Xupeng Miao, Yu He, Liang Wang, Zhi Yang, Bin Cui.
    IEEE International Conference on Data Engineering.
    ICDE 2022 (Industry Track), CCF-A.

  14. Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-aware Deep Architecture [Paper][Code]
    Xupeng Miao*, Wentao Zhang*, Yingxia Shao, Lei Chen, Ce Zhang, Jiawei Jiang, Bin Cui.
    IEEE International Conference on Data Engineering.
    ICDE (Extended Abstract) 2022, CCF-A.

  15. Efficient End-to-End AutoML via Scalable Search Space Decomposition. [Paper][Code[Doc]]
    Yang Li, Yu Shen, Wentao Zhang, Ce Zhang, Bin Cui.
    The International Journal on Very Large Data Bases.
    VLDBJ 2022, CCF-A.

  16. AutoDC: an Automatic Machine Learning Framework for Disease Classification [Paper]
    Yang Bai, Yang Li, Yu Shen, Mingyu Yang, Wentao Zhang, Bin Cui.
    Bioinformatics.
    Bioinformatics 2022, CCF-B.

  17. K-Core Decomposition on Super Large Graphs with Limited Resources [Paper]
    Shicheng Gao, Jie Xu, Xiaosen Li, Fangcheng Fu, Wentao Zhang, Wen Ouyang, Yangyu Tao and Bin Cui.
    The 37th ACM/SIGAPP Symposium On Applied Computing.
    ACM SAC 2022.

2021

  1. RIM: Reliable Influence-based Active Learning on Graphs [Paper][Code]
    Wentao Zhang, Yexin Wang, Zhenbang You, Meng Cao, Ping Huang, Jiulong Shan, Zhi Yang, Bin Cui.
    Thirty-fifth Conference on Neural Information Processing Systems.
    NeurIPS 2021, CCF-A, Spotlight Presentation, Acceptance Rate: < 3%.

  2. Node Dependent Local Smoothing for Scalable Graph Learning [Paper][Code]
    Wentao Zhang, Mingyu Yang, Zeang Sheng, Yang Li, Wen Ouyang, Yangyu Tao, Zhi Yang, Bin Cui.
    Thirty-fifth Conference on Neural Information Processing Systems.
    NeurIPS 2021, CCF-A, Spotlight Presentation, Acceptance Rate: < 3%.

  3. Grain: Improving Data Efficiency of Graph Neural Networks via Diversified Influence Maximization [Paper][Code]
    Wentao Zhang, Zhi Yang, Yexin Wang, Yu Shen, Yang Li, Liang Wang, Bin Cui.
    International Conference on Very Large Data Bases.
    VLDB 2021, CCF-A.

  4. Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-aware Deep Architecture [Paper][Code]
    Xupeng Miao*, Wentao Zhang*, Yingxia Shao, Lei Chen, Ce Zhang, Jiawei Jiang, Bin Cui.
    IEEE Transactions on Knowledge and Data Engineering.
    TKDE 2021, CCF-A.

  5. DeGNN: Characterizing and Improving Graph Neural Networks with Graph Decomposition [Paper][Code]
    Xupeng Miao*, Nezihe Merve Gürel*, Wentao Zhang*, …, Shuai Zhang, Yujing Wang, Bin Cui, Ce Zhang.
    SIGKDD Conference on Knowledge Discovery and Data Mining.
    SIGKDD 2021, CCF-A, Top #1 conference in Data Mining.

  6. ROD: Reception-aware Online Distillation for Sparse Graphs [Paper][Code]
    Wentao Zhang, Jiang Yuezihan, Yang Li, Zeang Sheng, Yu Shen, Xupeng Miao, Liang Wang, Zhi Yang, Bin Cui
    SIGKDD Conference on Knowledge Discovery and Data Mining.
    SIGKDD 2021, CCF-A, Top #1 conference in Data Mining .

  7. ALG: Fast and Accurate Active Learning Framework for Graph Convolutional Networks [Paper][Code]
    Wentao Zhang, Yu Shen, Yangli, Lei Chen, Zhi Yang, Bin Cui
    ACM SIGMOD International Conference on Management of Data.
    SIGMOD 2021, CCF-A, Top #1 conference in Data Bases.

  8. Distributed Optimization and Implementation of Graph Embedding Algorithms [Paper][Code]
    Wentao Zhang, Bin Yuan, ZhiPeng Zhang, Bin Cui.
    Journal of Software.
    JOS 2021, CCF-A.

  9. VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition [Paper][Code[Doc]]
    Yang Li, Yu Shen, Wentao Zhang, …, Wentao Wu, Ce Zhang, Bin Cui.
    International Conference on Very Large Data Bases.
    VLDB 2021, CCF-A.

  10. OpenBox: A Generalized Black-box Optimization Service [Paper][Code][Doc]
    Yang Li, Yu Shen, Wentao Zhang, …, Ce Zhang, Bin Cui.
    SIGKDD Conference on Knowledge Discovery and Data Mining.
    SIGKDD 2021, CCF-A, Top #1 conference in Data Mining.

  11. Enhanced review-based rating prediction by exploiting aside information and user influence [Paper][Code]
    Shiwen Wu, Yuanxing Zhang, Wentao Zhang, Kaigui Bian, Bin Cui.
    Knowledge Based System.
    KBS 2021, JCR Q1, IF=8.038.

2020

  1. Reliable Data Distillation on Graph Convolutional Network [Paper][Code]
    Wentao Zhang*, Xupeng Miao*, Yingxia Shao, Jiawei Jiang, Lei Chen, Olivier Ruas, Bin Cui
    ACM SIGMOD International Conference on Management of Data.
    SIGMOD 2020, CCF-A, Top #1 conference in Data Bases.

  2. Efficient Diversity-Driven Ensemble for Deep Neural Networks [Paper][Code]
    Wentao Zhang, Jiawei Jiang, Yingxia Shao, Bin Cui.
    IEEE International Conference on Data Engineering.
    ICDE 2020, CCF-A.

  3. Snapshot Boosting: A Fast Ensemble Framework for Deep Neural Networks [Paper][Code]
    Wentao Zhang, Jiawei Jiang, Yingxia Shao, Bin Cui.
    Sci China Inf Sci.
    SCIS 2020, CCF-A.

Preprints

  1. Distributed Graph Neural Network Training: A Survey [Paper]
    Yingxia Shao, Hongzheng Li, Xizhi Gu, Hongbo Yin, Yawen Li, Xupeng Miao, Wentao Zhang, Bin Cui, Lei Chen.
    arXiv:2211.00216, 2022. (arXiv preprint).

  2. Efficient Graph Neural Network Inference at Large Scale [Paper]
    Xinyi Gao, Wentao Zhang#, Yingxia Shao, Quoc Viet Hung Nguyen, Bin Cui, Hongzhi Yin.
    arXiv:2211.00495, 2022. (arXiv preprint).

  3. Diffusion Models: A Comprehensive Survey of Methods [Paper][Code]
    Ling Yang, Zhilong Zhang, Shenda Hong, Runsheng Xu, Yue Zhao, Yingxia Shao, Wentao Zhang#, Ming-Hsuan Yang, Bin Cui.
    arXiv:2209.00796, 2022. (arXiv preprint).

  4. Evaluating Deep Graph Neural Networks [Paper][Code]
    Wentao Zhang, Zeang Sheng, Yuezihan Jiang, Yikuan Xia, Jun Gao, Zhi Yang, Bin Cui.
    arXiv:2011.02260, 2020. (arXiv preprint).

  5. Graph Attention Multi-Layer Perceptron [Paper][Code]
    Wentao Zhang, Ziqi Yin, Zeang Sheng, Wen Ouyang, Xiaosen Li, Yangyu Tao, Zhi Yang, Bin Cui.
    arXiv:2108.10097, 2021. (arXiv preprint).

  6. GMLP: Building Scalable and Flexible Graph Neural Networks with Feature-Message Passing [Paper][Code]
    Wentao Zhang, Yu Shen, Zheyu Lin, Yang Li, Xiaosen Li, Wen Ouyang, Yangyu Tao, Zhi Yang, Bin Cui.
    arXiv:2108.00955, 2021. (arXiv preprint).