Publications

@article{jin2024forgettable,
  title     = {Forgettable Federated Linear Learning with Certified Data Removal},
  author    = {Jin, Ruinan and Chen, Minghui and Zhang, Qiong and Li, Xiaoxiao},
  journal   = {IEEE Transactions on Neural Networks and Learning Systems},
  year      = {2024},
  publisher = {IEEE},
  doi       = {10.1109/TNNLS.2025.3578621}
}

@article{zhang2026byzantine,
  author  = {Zhang, Qiong and Tan, Yan Shuo and Chen, Jiahua},
  title   = {Byzantine-tolerant distributed learning of finite mixture models},
  journal = {Journal of the Royal Statistical Society Series B: Statistical Methodology},
  pages   = {qkag065},
  year    = {2026},
  month   = {04},
  doi     = {10.1093/jrsssb/qkag065},
  url     = {https://doi.org/10.1093/jrsssb/qkag065}
}

@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}
}

@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}
}

@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}
}

@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},
  volume  = {45},
  number  = {1},
  pages   = {81--99},
  year    = {2019}
}

@article{phan2019highlighting,
  title     = {Highlighting discrepancies in walking prediction accuracy for patients with traumatic spinal cord injury},
  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}
}

@inproceedings{wang2026beyond,
  title     = {Beyond Aggregation: Guiding Clients in Heterogeneous Federated Learning},
  author    = {Wang, Zijian and Zhang, Xiaofei and Zhang, Xin and Liu, Yukun and Zhang, Qiong},
  booktitle = {The Fourteenth International Conference on Learning Representations},
  year      = {2026},
  url       = {https://openreview.net/forum?id=RZT1ixYGk1}
}

@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}
}

@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}
}

@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}
}

@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}
}

@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}
}

@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}
}