Yu Xingrui


Research Area
  • Imitation Learning
  • Robust Learning


  • ICML Travel Award 2019
  • NeurIPS Travel Award 2018


1. Xingrui Yu, Yueming LYU, Ivor W. Tsang. Intrinsic Reward Driven Imitation Learning via Generative Model. International Conference on Machine Learning (ICML), 2020.

2. Bo Han, Gang Niu, Xingrui Yu, Quanming Yao, Miao Xu, Ivor W. Tsang, Masashi Sugiyama. SIGUA: Forgetting May Make Learning with Noisy Labels More Robust. International Conference on Machine Learning (ICML), 2020.

3. Xingrui Yu, Bo Han, Jiangchao Yao, Gang Niu, Ivor W. Tsang, Masashi Sugiyama. How does Disagreement Help Generalization against Label Corruption? International Conference on Machine Learning (ICML), 2019.

4. Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor Tsang, and Masashi Sugiyama. Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels. Advances in Neural Information Processing Systems (NeurIPS), 2018.

5. Xingrui Yu, He Zhang, Chunbo Luo, Hairong Qi, and Peng Ren. Oil Spill Segmentation via Adversarial f -Divergence Learning. IEEE Transactions on Geoscience and Remote Sensing (TGRS), 56(9): 4973-4988, 2018.

Research Services

  • Conference Reviewer/(Senior) Program Committee:
    ICLR-2020, ICLR-2021, ICLR-2022, ICLR-2023
    ICML-2019, ICML-2020, ICML-2021, ICML-2022, ICML-2023
    NeurIPS-2019, NeurIPS-2020, NeurIPS-2022, NeruIPS-2023
    AAAI-2020, ECAI-2020
    IJCAI-2019, IJCAI-2020, IJCAI-2021, IJCAI-2022, IJCAI-2023
    ACML-2019, ACML-2020, ACML-2021, ACML-2022

  • Journal Reviewer:
    IEEE TPAMI (IEEE Transactions on Pattern Analysis and Machine Intelligence)
    Machine Learning
    Pattern Recognition