You can also browse my Google Scholar profile.

2024

  • Huaijun Jiang, Yu Shen, Yang Li, Beicheng Xu, Sixian Du, Wentao Zhang, Ce Zhang, Bin Cui. Openbox: A Python Toolkit for Generalized Black-box Optimization. JMLR 2024.
  • Wentao Zhang, Guochen Yan, Yu Shen, Yang Ling, Yangyu Tao, Bin Cui, Jian Tang. NPA: Improving Large-scale Graph Neural Networks with Non-parametric Attention. SIGMOD 2024.

2023

  • Yu Shen, Xinyuyang Ren, Yupeng Lu, Huaijun Jiang, Huanyong Xu, Di Peng, Yang Li, Wentao Zhang, and Bin Cui. Rover: An Online Spark SQL Tuning Service via Generalized Transfer Learning. KDD 2023.
  • Yang Li, Huaijun Jiang, Yu Shen, Yide Fang, Xiaofeng Yang, Danqing Huang, Xinyi Zhang, Wentao Zhang, Ce Zhang, Peng Chen, and Bin Cui. Towards General and Efficient Online Tuning for Spark. VLDB 2023.
  • Yu Shen, Yang Li, Jian Zheng, Wentao Zhang, Peng Yao, Jixiang Li, Sen Yang, Ji Liu, and Bin Cui. ProxyBO: Accelerating Neural Architecture Search via Bayesian Optimization with Zero-Cost Proxies. AAAI Oral 2023.

2022

  • Yu Shen, Yupeng Lu, Yang Li, Yaofeng Tu, Wentao Zhang, and Bin Cui. DivBO: Diversity-aware CASH for Ensemble Learning. NeurIPS 2022.
  • Wentao Zhang, Zheyu Lin, Yu Shen, Yang Li, Zhi Yang, and Bin Cui. Deep and Flexible Graph Neural Architecture Search. ICML 2022.
  • Wentao Zhang, Zeang Sheng, Mingyu Yan, Yang Li, Yu Shen, Zhi Yang, and Bin Cui. NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning. ICML 2022.
  • Yang Li, Yu Shen, Wentao Zhang, Ce Zhang, and Bin Cui. VolcanoML: speeding up end-to-end AutoML via scalable search space decomposition. VLDBJ 2022.
  • Yang Li, Yu Shen, Huaijun Jiang, Wentao Zhang, Zhi Yang, Ce Zhang, and Bin Cui. TransBO: Hyperparameter Optimization via Two-Phase Transfer Learning. KDD 2022.
  • Yang Li, Yu Shen, Huaijun Jiang, Tianyi Bai, Wentao Zhang, Ce Zhang, and Bin Cui. Transfer Learning based Search Space Design for Hyperparameter Tuning. KDD 2022.
  • Wentao Zhang, Yu Shen, Zheyu Lin, Yang Li, Xiaosen Li, Wen Ouyang, Yangyu Tao, Zhi Yang, and Bin Cui. PaSca: a Graph Neural Architecture Search System under the Scalable Paradigm. WWW 2022. Best Student Paper!
  • Yang Li, Yu Shen, Huaijun Jiang, Wentao Zhang, Jixiang Li, Ji Liu, Ce Zhang, and Bin Cui. Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale. VLDB 2022.

2021

  • Wentao Zhang, Yuezihan Jiang, Yang Li, Zeang Sheng, Yu Shen, Xupeng Miao, Liang Wang, Zhi Yang, and Bin Cui. ROD: Reception-aware Online Distillation for Sparse Graphs. KDD 2021.
  • Yang Li, Yu Shen, Wentao Zhang, Yuanwei Chen, Huaijun Jiang, Mingchao Liu, Jiawei Jiang, Jinyang Gao, Wentao Wu, Zhi Yang, Ce Zhang, and Bin Cui. OpenBox: A Generalized Black-box Optimization Service. KDD 2021.
  • Wentao Zhang, Zhi Yang, Yexin Wang, Yu Shen, Yang Li, Liang Wang, and Bin Cui. Grain: Improving Data Efficiency of Graph Neural Networks via Diversified Influence Maximization. VLDB 2021.
  • Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang, Bolin Ding, Yang Li, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, and Bin Cui. VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition. VLDB 2021.
  • Wentao Zhang, Yu Shen, Yang Li, Lei Chen, Zhi Yang, and Bin Cui. ALG: Fast and Accurate Active Learning Framework for Graph Convolutional Networks. SIGMOD 2021.
  • Yang Li, Yu Shen, Jiawei Jiang, Jinyang Gao, Ce Zhang, and Bin Cui. MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements. AAAI Spotlight 2021.