Publications

* indicates equal contributions.

Conference & journal articles

1. Rethinking the Evaluation Protocol of Domain Generalization

   Han Yu, Xingxuan Zhang, Renzhe Xu, Jiashuo Liu, Yue He, and Peng Cui

   In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2024)
2. Flatness-Aware Minimization for Domain Generalization

   Xingxuan Zhang, Renzhe Xu, Han Yu, Yancheng Dong, Pengfei Tian, and Peng Cui

   In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV 2023)
3. Competing for Shareable Arms in Multi-Player Multi-Armed Bandits

   Renzhe Xu*, Haotian Wang*, Xingxuan Zhang, Bo Li, and Peng Cui

   In Proceedings of the 40th International Conference on Machine Learning (ICML 2023)

   Code
4. Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization

   Xingxuan Zhang*, Renzhe Xu*, Han Yu, Hao Zou, and Peng Cui

   In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2023)

   Highlights (2.6%)

   Code
5. NICO++: Towards Better Benchmarking for Domain Generalization

   Xingxuan Zhang*, Yue He*, Renzhe Xu, Han Yu, Zheyan Shen, and Peng Cui

   In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2023)

   Code
6. Measure the Predictive Heterogeneity

   Jiashuo Liu, Jiayun Wu, Renjie Pi, Renzhe Xu, Xingxuan Zhang, Bo Li, and Peng Cui

   In International Conference on Learning Representations (ICLR 2023)
7. Factual Observation Based Heterogeneity Learning for Counterfactual Prediction

   Hao Zou, Haotian Wang, Renzhe Xu, Bo Li, Jian Pei, Junjian Ye, and Peng Cui

   In Second Conference on Causal Learning and Reasoning (CLeaR 2023)
8. Covariate-Shift Generalization via Random Sample Weighting

   Yue He, Xinwei Shen, Renzhe Xu, Tong Zhang, Yong Jiang, Wenchao Zou, and Peng Cui

   In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2023)

   Code
9. Stable Learning via Sparse Variable Independence

   Han Yu, Peng Cui, Yue He, Zheyan Shen, Yong Lin, Renzhe Xu, and Xingxuan Zhang

   In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2023)

   Oral

   Code
10. Product Ranking for Revenue Maximization with Multiple Purchases

    Renzhe Xu, Xingxuan Zhang, Bo Li, Yafeng Zhang, Xiaolong Chen, and Peng Cui

    In Advances in Neural Information Processing Systems (NeurIPS 2022)

    Code
11. NICO Challenge: Out-of-Distribution Generalization for Image Recognition Challenges

    Xingxuan Zhang, Yue He, Tan Wang, Jiaxin Qi, Han Yu, Zimu Wang, Jie Peng, Renzhe Xu, Zheyan Shen, Yulei Niu, Hanwang Zhang, and Peng Cui

    In European conference on computer vision workshop (ECCV Workshop 2022)
12. A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization

    Renzhe Xu, Xingxuan Zhang, Zheyan Shen, Tong Zhang, and Peng Cui

    In Proceedings of the 39th International Conference on Machine Learning (ICML 2022)

    Code
13. Model Agnostic Sample Reweighting for Out-of-Distribution Learning

    Xiao Zhou*, Yong Lin*, Renjie Pi*, Weizhong Zhang, Renzhe Xu, Peng Cui, and Tong Zhang

    In Proceedings of the 39th International Conference on Machine Learning (ICML 2022)

    Code
14. Towards Unsupervised Domain Generalization

    Xingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui, Zheyan Shen, and Haoxin Liu

    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022)
15. Regulatory Instruments for Fair Personalized Pricing

    Renzhe Xu, Xingxuan Zhang, Peng Cui, Bo Li, Zheyan Shen, and Jiazheng Xu

    In Proceedings of the ACM Web Conference 2022 (WWW 2022)

    Code Scientific American Montreal AI Ethics Institute
16. Daring: Differentiable Causal Discovery with Residual Independence

    Yue He, Peng Cui, Zheyan Shen, Renzhe Xu, Furui Liu, and Yong Jiang

    In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD 2021)

    Code
17. Deep Stable Learning for Out-of-distribution Generalization

    Xingxuan Zhang, Peng Cui, Renzhe Xu, Linjun Zhou, Yue He, and Zheyan Shen

    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2021)

    Code
18. Algorithmic Decision Making with Conditional Fairness

    Renzhe Xu, Peng Cui, Kun Kuang, Bo Li, Linjun Zhou, Zheyan Shen, and Wei Cui

    In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2020)

    Code
19. Uncovering the Co-driven Mechanism of Social and Content Links in User Churn Phenomena

    Yunfei Lu, Linyun Yu, Peng Cui, Chengxi Zang, Renzhe Xu, Yihao Liu, Lei Li, and Wenwu Zhu

    In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2019)

Preprints

1. PPA-Game: Characterizing and Learning Competitive Dynamics Among Online Content Creators

   Renzhe Xu, Haotian Wang, Xingxuan Zhang, Bo Li, and Peng Cui

   arXiv preprint arXiv:2403.15524
2. On the Out-Of-Distribution Generalization of Multimodal Large Language Models

   Xingxuan Zhang*, Jiansheng Li*, Wenjing Chu, Junjia Hai, Renzhe Xu, Yuqing Yang, Shikai Guan, Jiazheng Xu, and Peng Cui

   arXiv preprint arXiv:2402.06599
3. Towards Domain Generalization in Object Detection

   Xingxuan Zhang, Zekai Xu, Renzhe Xu, Jiashuo Liu, Peng Cui, Weitao Wan, Chong Sun, and Chen Li

   arXiv preprint arXiv:2203.14387
4. Towards out-of-distribution generalization: A survey

   Jiashuo Liu*, Zheyan Shen*, Yue He, Xingxuan Zhang, Renzhe Xu, Han Yu, and Peng Cui

   arXiv preprint arXiv:2108.13624