Publications

πŸ“§ Corresponding author. * Equal contribution or alphabetical order. πŸŽ“ student that I supervised/co-supervised for the project

πŸ—οΈ Work in progress
  • Neyman-Pearson multiclass classification under label noise
    Qiong Zhang, Qinglong Tian, Pengfei Li
πŸ“œ Preprints
  • TabClustPFN: A prior-fitted network for tabular data clustering
    Tianqi ZhaoπŸŽ“, Guanyang Wang, Yan Shuo Tan, Qiong ZhangπŸ“§
    πŸ“š arXiv
  • Minimum Wasserstein distance estimator under covariate shift: closed form and super-efficiency
    Junjun Lang, Qiong ZhangπŸ“§, Yukun LiuπŸ“§
    πŸ“š arXiv
  • Reference image-guided comparative vision-language models for medical diagnosis
    Ruinan Jin, Gexin Huang, Xinwei Shen, Qiong Zhang, Yan Shuo Tan, Xiaoxiao Li
    πŸ“š arXiv
  • FedMT: Federated learning with mixed-type labels
    Qiong Zhang, Jing Peng*, Xin Zhang*, Aline Talhouk, Gang Niu, Xiaoxiao Li
    πŸ“š arXiv
  • TabPFN: One model to rule them all?
    Qiong Zhang*, Yan Shuo Tan*, Qinglong Tian*, Pengfei Li
    Major revision at JASA
    πŸ“š arXiv πŸ’» Code
  • Byzantine-tolerant distributed learning of finite mixture models
    Qiong Zhang*, Yan Shuo Tan*, Jiahua Chen
    R&R at JRSSB
    πŸ“š arXiv πŸ’» Code πŸ“š Slides
  • Forgettable federated linear learning with certified data removal
    Ruinan JinπŸŽ“, Minghui ChenπŸŽ“, Qiong ZhangπŸ“§, Xiaoxiao Li
    Minor revision at IEEE TNNLS
    πŸ“š arXiv πŸ’» Code
βœ… Published
  • Beyond aggregation: Guiding clients in heterogeneous federated learning
    Zijian WangπŸŽ“, Xiaofei Zhang, Xin Zhang, Yukun Liu, Qiong ZhangπŸ“§
    ICLR, 2026
    πŸ“„ Openreview πŸ“š arXiv πŸ’» Code
  • Gaussian Herding across Pens: An optimal transport perspective on global Gaussian reduction for 3DGS
    Tao Wang*πŸŽ“, Mengyu Li*πŸŽ“, Geduo ZengπŸŽ“, Cheng MengπŸ“§, Qiong ZhangπŸ“§
    NeurIPS (spotlight), 2025
    πŸ“„ Openreview πŸ“š arXiv πŸ’» Code πŸ“Š Poster 
    @inproceedings{wang2025gaussian,
  title={{Gaussian Herding across Pens: An optimal transport perspective on global Gaussian reduction for 3DGS}},
  author={Wang, Tao and Li, Mengyu and Zeng, Geduo and Meng, Cheng and Zhang, Qiong},
  booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems},
  year={2025},
  }
  • S4M: S4 for multivariate time series forecasting with Missing values
    Jing PengπŸŽ“, Meiqi Yang, Qiong ZhangπŸ“§, Xiaoxiao Li
    ICLR, 2025
    πŸ“„ Openreview πŸ“š arXiv πŸ’» Code πŸ“Š Poster 
    @inproceedings{peng2025s4m,
  title={S4M: S4 for multivariate time series forecasting with Missing values},
  author={Peng, Jing and Yang, Meiqi and Zhang, Qiong and Li, Xiaoxiao},
  booktitle={The Thirteenth International Conference on Learning Representations},
  year={2025},
  url={https://openreview.net/forum?id=BkftcwIVmR}
  }
  • Gaussian mixture reduction with composite transportation divergence
    Qiong Zhang, Archer Gong Zhang, Jiahua Chen
    IEEE Transactions on Information Theory, 2024
    πŸ“„ Journal πŸ“š arXiv πŸ’» Code πŸ“š Slides 
    @article{zhang2024gaussian,
  title={Gaussian Mixture Reduction With Composite Transportation Divergence},
  author={Zhang, Qiong and Zhang, Archer Gong and Chen, Jiahua},
  journal={IEEE Transactions on Information Theory},
  year={2024},
  volume={70},
  number={7},
  pages={5191-5212},
  doi={10.1109/TIT.2023.3323346}
  }
  • Distributed learning of finite mixture models
    Qiong Zhang, Jiahua Chen
    JMLR, 2022
    πŸ“„ Journal πŸ“š arXiv πŸ’» Code πŸŽ₯ Talk πŸ“š Slides πŸ“Š Poster 
    @article{zhang2022distributed,
  title={Distributed Learning of Finite Gaussian Mixtures},
  author={Zhang, Qiong and Chen, Jiahua},
  journal={Journal of Machine Learning Research},
  year={2022},
  volume={23},
  number={1},
  pages={4265--4304},
  url={http://jmlr.org/papers/v23/21-0093.html}
  }
  • Minimum Wasserstein distance estimator under finite location-scale mixtures
    Qiong Zhang, Jiahua Chen
    Advances and Innovations in Statistics and Data Science, 2022
    πŸ“„ Chapter πŸ“š arXiv 
    @incollection{zhang2022minimum,
  title={Minimum Wasserstein distance estimator under finite location-scale mixtures},
  author={Zhang, Qiong and Chen, Jiahua},
  booktitle={Advances and Innovations in Statistics and Data Science},
  pages={69--98},
  year={2022},
  publisher={Springer}
  }
  • Robustness of Gaussian mixture reduction for split-and-conquer learning of finite Gaussian mixtures
    Qiong Zhang, Jiahua Chen
    ICSTA, 2021
    πŸ“„ Proceedings πŸŽ₯ Talk 
    @inproceedings{zhang2021robustness,
  title={Robustness of Gaussian Mixture Reduction for Split-and-Conquer Learning of Finite Gaussian Mixtures},
  author={Zhang, Qiong and Chen, Jiahua},
  booktitle={Proceedings of the 3rd International Conference on Statistics: Theory and Applications (ICSTA'21)},
  year={2021}
  }
  • Boosting the generalization capability in cross-domain few-shot learning via noise-enhanced supervised autoencoder
    Hanwen Liang*, Qiong Zhang*, Peng Dai, Juwei Lu
    ICCV, 2021
    πŸ“„ Proceedings πŸ“š arXiv πŸ“Š Poster 
    @inproceedings{liang2021boosting,
  title={Boosting the Generalization Capability in Cross-Domain Few-shot Learning via Noise-enhanced Supervised Autoencoder},
  author={Liang, Hanwen and Zhang, Qiong and Dai, Peng and Lu, Juwei},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={9424--9434},
  year={2021}
  }
  • Classification beats regression: Counting of cells from greyscale microscopic images based on annotation-free training samples
    Xin Ding*, Qiong Zhang*, William J Welch
    CAAI International Conference on Artificial Intelligence, 2021
    πŸ“„ Proceedings πŸ“š arXiv πŸ’» Code πŸ“Š Poster 
    @inproceedings{ding2021classification,
  title={Classification Beats Regression: Counting of Cells from Greyscale Microscopic Images Based on Annotation-Free Training Samples},
  author={Ding, Xin and Zhang, Qiong and Welch, William J},
  booktitle={CAAI International Conference on Artificial Intelligence},
  pages={662--673},
  year={2021},
  organization={Springer}
  }
  • Small area quantile estimation via spline regression and empirical likelihood
    Zhanshou Chen, Jiahua Chen, Qiong Zhang
    Survey Methodology, 2019
    πŸ“„ Journal 
    @article{chen2019small,
  title={Small area quantile estimation via spline regression and empirical likelihood},
  author={Chen, Zhanshou and Chen, Jiahua and Zhang, Qiong},
  journal={Survey Methodology 45-1},
  volume={45},
  number={1},
  pages={81--99},
  year={2019}
  }
  • Highlighting discrepancies in walking prediction accuracy for patients with traumatic spinal cord injury: an evaluation of validated prediction models using a Canadian multicenter spinal cord injury registry
    Philippe Phan, Brandon Budhram, Qiong Zhang, Carly S Rivers, Vanessa K Noonan, Tova Plashkes, Eugene K Wai, Jérôme Paquet, Darren M Roffey, Eve Tsai
    The Spine Journal, 2019
    πŸ“„ Journal 
    @article{phan2019highlighting,
  title={Highlighting discrepancies in walking prediction accuracy for patients with traumatic spinal cord injury: an evaluation of validated prediction models using a {C}anadian multicenter spinal cord injury registry},
  author={Phan, Philippe and Budhram, Brandon and Zhang, Qiong and Rivers, Carly S and Noonan, Vanessa K and Plashkes, Tova and Wai, Eugene K and Paquet, J{\'e}r{\^o}me and Roffey, Darren M and Tsai, Eve and others},
  journal={The Spine Journal},
  volume={19},
  number={4},
  pages={703--710},
  year={2019},
  publisher={Elsevier}
  }
  • Generating handwritten Chinese characters using CycleGAN
    Bo Chang*, Qiong Zhang*, Shenyi Pan, Lili Meng
    WACV, 2018
    πŸ“„ Proceedings πŸ“š arXiv πŸ’» Code πŸŽ₯ Talk 
    @inproceedings{chang2018generating,
  title={Generating handwritten chinese characters using cyclegan},
  author={Chang, Bo and Zhang, Qiong and Pan, Shenyi and Meng, Lili},
  booktitle={2018 IEEE Winter Conference on Applications of Computer Vision (WACV)},
  pages={199--207},
  year={2018},
  organization={IEEE}
  }

Collaborators