Publications
π§ Corresponding author. * Equal contribution or alphabetical order. π student that I supervised/co-supervised for the project
ποΈ Work in progress
- Minimum Wasserstein distance estimator under covariate shift: closed form and super-efficiency
- Neyman-Pearson multiclass classification under label noise
π Preprints
- Reference image-guided comparative vision-language models for medical diagnosis
- FedMT: Federated learning with mixed-type labels
- Beyond aggregation: Guiding clients in heterogeneous federated learning
- Forgettable federated linear learning with certified data removalR&R at IEEE TNNLS
- TabPFN: One model to rule them all?Major revision at JASA
- Byzantine-tolerant distributed learning of finite mixture modelsR&R at JRSSB
β Published
- Gaussian Herding across Pens: An optimal transport perspective on global Gaussian reduction for 3DGSNeurIPS (spotlight), 2025
@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 valuesICLR, 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} } - Gaussian mixture reduction with composite transportation divergenceIEEE Transactions on Information Theory, 2024
@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 modelsJMLR, 2022
@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 mixturesAdvances and Innovations in Statistics and Data Science, 2022
@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 mixturesICSTA, 2021
@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 autoencoderICCV, 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} } - Classification beats regression: Counting of cells from greyscale microscopic images based on annotation-free training samplesCAAI International Conference on Artificial Intelligence, 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} } - Small area quantile estimation via spline regression and empirical likelihoodSurvey Methodology, 2019
@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 registryThe Spine Journal, 2019
@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 CycleGANWACV, 2018
@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} }