| Estimating a change point in a sequence of very high-dimensional covariance matrices H Dette, G Pan, Q Yang Journal of the American Statistical Association 117 (537), 444-454, 2022 | 43 | 2022 |
| Large dimensional empirical likelihood B Chen, G Pan, Q Yang, W Zhou Statistica Sinica, 1659-1677, 2015 | 24 | 2015 |
| Weighted statistic in detecting faint and sparse alternatives for high-dimensional covariance matrices Q Yang, G Pan Journal of the American Statistical Association 112 (517), 188-200, 2017 | 23 | 2017 |
| Power iteration for tensor PCA J Huang, DZ Huang, Q Yang, G Cheng Journal of Machine Learning Research 23 (128), 1-47, 2022 | 22 | 2022 |
| Universal rank inference via residual subsampling with application to large networks X Han, Q Yang, Y Fan The Annals of Statistics 51 (3), 1109-1133, 2023 | 20 | 2023 |
| A unified matrix model including both CCA and F matrices in multivariate analysis: The largest eigenvalue and its applications X Han, G Pan, Q Yang | 19 | 2018 |
| Quadratic discriminant analysis under moderate dimension Q Yang, G Cheng arXiv preprint arXiv:1808.10065, 2018 | 6 | 2018 |
| On high-dimensional change point problem BS Jin, GM Pan, Q Yang, W Zhou Science China Mathematics 59, 2355-2378, 2016 | 5 | 2016 |
| CLT for Generalized Linear Spectral Statistics of High-dimensional Sample Covariance Matrices and Applications Y Hu, Q Yang, X Han arXiv preprint arXiv:2406.05811, 2024 | | 2024 |
| Individual-centered Partial Information in Social Networks X Han, YXR Wang, Q Yang, X Tong Journal of Machine Learning Research 25 (230), 1-60, 2024 | | 2024 |
| Appendix for the submission entitled “Weighted Statistic in Detecting Faint and Sparse Alternatives for High-dimensional Covariance Matrices” Q Yang, G Pan | | |
