| Optimal subsampling algorithms for big data regressions M Ai, J Yu, H Zhang, HY Wang Statistica Sinica 31 (2), 749-772, 2021 | 90 | 2021 |
| Optimal distributed subsampling for maximum quasi-likelihood estimators with massive data J Yu, HY Wang, M Ai, H Zhang Journal of the American Statistical Association 117 (537), 265-276, 2022 | 89 | 2022 |
| Optimal subsampling for large-scale quantile regression M Ai, F Wang, J Yu, H Zhang Journal of Complexity 62, 101512, 2021 | 44 | 2021 |
| Optimal subsampling algorithms for big data generalized linear models M Ai, J Yu, H Zhang, H Wang arXiv preprint arXiv:1806.06761, 2018 | 21 | 2018 |
| A review on design inspired subsampling for big data J Yu, M Ai, Z Ye Statistical Papers 65 (2), 467-510, 2024 | 17 | 2024 |
| Subdata selection algorithm for linear model discrimination J Yu, HY Wang Statistical Papers 63 (6), 1883-1906, 2022 | 14 | 2022 |
| Sufficient dimension reduction for classification using principal optimal transport direction C Meng, J Yu, J Zhang, P Ma, W Zhong Advances in Neural Information Processing Systems 33, 4015-4028, 2020 | 14 | 2020 |
| Hilbert curve projection distance for distribution comparison T Li, C Meng, H Xu, J Yu IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 12 | 2024 |
| Efficient approximation of Gromov-Wasserstein distance using importance sparsification M Li, J Yu, H Xu, C Meng Journal of Computational and Graphical Statistics 32 (4), 1512-1523, 2023 | 11 | 2023 |
| Smoothing splines approximation using Hilbert curve basis selection C Meng, J Yu, Y Chen, W Zhong, P Ma Journal of Computational and Graphical Statistics 31 (3), 802-812, 2022 | 10 | 2022 |
| CONGO²: Scalable online anomaly detection and localization in power electronics networks J Yu, H Cheng, J Zhang, Q Li, S Wu, W Zhong, J Ye, W Song, P Ma IEEE internet of things journal 9 (15), 13862-13875, 2022 | 9 | 2022 |
| An optimal transport approach for selecting a representative subsample with application in efficient kernel density estimation J Zhang, C Meng, J Yu, M Zhang, W Zhong, P Ma Journal of Computational and Graphical Statistics 32 (1), 329-339, 2023 | 8 | 2023 |
| Information-based optimal subdata selection for non-linear models J Yu, J Liu, HY Wang Statistical Papers 64 (4), 1069-1093, 2023 | 4 | 2023 |
| Importance sparsification for Sinkhorn algorithm M Li, J Yu, T Li, C Meng arXiv preprint arXiv:2306.06581, 2023 | 4 | 2023 |
| Optimal designs for dose–response models with linear effects of covariates J Yu, X Kong, M Ai, KL Tsui Computational statistics & data analysis 127, 217-228, 2018 | 3 | 2018 |
| Scalable model-free feature screening via sliced-wasserstein dependency T Li, J Yu, C Meng Journal of Computational and Graphical Statistics 32 (4), 1501-1511, 2023 | 2 | 2023 |
| Details of Single-Molecule Force Spectroscopy Data Decoded by a Network-Based Automatic Clustering Algorithm H Cheng, J Yu, Z Wang, P Ma, C Guo, B Wang, W Zhong, B Xu The Journal of Physical Chemistry B 125 (34), 9660-9667, 2021 | 2 | 2021 |
| Fast calibration for computer models with massive physical observations S Lv, J Yu, Y Wang, J Du SIAM/ASA Journal on Uncertainty Quantification 11 (3), 1069-1104, 2023 | 1 | 2023 |
| A reinforced learning approach to optimal design under model uncertainty M Ai, H Dette, Z Liu, J Yu arXiv preprint arXiv:2303.15887, 2023 | 1 | 2023 |
| LOCALLY D-OPTIMAL DESIGNS FOR HIERARCHICAL RESPONSE EXPERIMENTS. M Ai, Z Ye, J Yu Statistica Sinica 33 (1), 2023 | 1 | 2023 |
