| Hybrid linear modeling via local best-fit flats T Zhang, A Szlam, Y Wang, G Lerman International journal of computer vision 100 (3), 217-240, 2012 | 239 | 2012 |
| Median k-flats for hybrid linear modeling with many outliers T Zhang, A Szlam, G Lerman 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV …, 2009 | 210 | 2009 |
| Robust computation of linear models by convex relaxation G Lerman, MB McCoy, JA Tropp, T Zhang Foundations of Computational Mathematics 15, 363-410, 2015 | 203* | 2015 |
| Sparse precision matrix estimation via lasso penalized d-trace loss T Zhang, H Zou Biometrika 99 (1), 1-18, 2012 | 172 | 2012 |
| CloudLeak: Large-Scale Deep Learning Models Stealing Through Adversarial Examples. H Yu, K Yang, T Zhang, YY Tsai, TY Ho, Y Jin NDSS 38, 102, 2020 | 148 | 2020 |
| A novel m-estimator for robust pca T Zhang, G Lerman The Journal of Machine Learning Research 15 (1), 749-808, 2014 | 143 | 2014 |
| Robust recovery of multiple subspaces by geometric lp minimization G Lerman, T Zhang | 113 | 2011 |
| Spectral clustering based on local PCA E Arias-Castro, G Lerman, T Zhang Journal of Machine Learning Research 18 (9), 1-57, 2017 | 97 | 2017 |
| Spectral clustering in the dynamic stochastic block model M Pensky, T Zhang | 93 | 2019 |
| Multivariate generalized Gaussian distribution: Convexity and graphical models T Zhang, A Wiesel, MS Greco IEEE Transactions on Signal Processing 61 (16), 4141-4148, 2013 | 91 | 2013 |
| Denoising and covariance estimation of single particle cryo-EM images T Bhamre, T Zhang, A Singer Journal of structural biology 195 (1), 72-81, 2016 | 69 | 2016 |
| A well-tempered landscape for non-convex robust subspace recovery T Maunu, T Zhang, G Lerman Journal of Machine Learning Research 20 (37), 1-59, 2019 | 64 | 2019 |
| Robust stochastic principal component analysis J Goes, T Zhang, R Arora, G Lerman Artificial Intelligence and Statistics, 266-274, 2014 | 57 | 2014 |
| Marčenko–Pastur law for Tyler’s M-estimator T Zhang, X Cheng, A Singer Journal of Multivariate Analysis 149, 114-123, 2016 | 55 | 2016 |
| Robust PCA by manifold optimization T Zhang, Y Yang Journal of Machine Learning Research 19 (80), 1-39, 2018 | 50 | 2018 |
| Randomized hybrid linear modeling by local best-fit flats T Zhang, A Szlam, Y Wang, G Lerman 2010 ieee computer society conference on computer vision and pattern …, 2010 | 49 | 2010 |
| Structured robust covariance estimation A Wiesel, T Zhang Foundations and Trends® in Signal Processing 8 (3), 127-216, 2015 | 48 | 2015 |
| Robust subspace recovery by Tyler's M-estimator T Zhang Information and Inference: A Journal of the IMA 5 (1), 1-21, 2016 | 46* | 2016 |
| Estimation of safe sensor measurements of autonomous system under attack RG Dutta, X Guo, T Zhang, K Kwiat, C Kamhoua, L Njilla, Y Jin Proceedings of the 54th Annual Design Automation Conference 2017, 1-6, 2017 | 45 | 2017 |
| Spectral clustering based on local PCA E Arias-Castro, G Lerman, T Zhang arXiv preprint arXiv:1301.2007, 2013 | 34 | 2013 |
