| Patterns and rates of exonic de novo mutations in autism spectrum disorders BM Neale, Y Kou, L Liu, A Ma’Ayan, KE Samocha, A Sabo, CF Lin, ... Nature 485 (7397), 242-245, 2012 | 1908 | 2012 |
| The huge package for high-dimensional undirected graph estimation in R T Zhao, H Liu, K Roeder, J Lafferty, L Wasserman The Journal of Machine Learning Research 13 (1), 1059-1062, 2012 | 544* | 2012 |
| SMART: Robust and efficient fine-tuning for pre-trained natural language models through principled regularized optimization H Jiang, P He, W Chen, X Liu, J Gao, T Zhao arXiv preprint arXiv:1911.03437 (ACL), 2019 | 266 | 2019 |
| A nonconvex optimization framework for low rank matrix estimation T Zhao, Z Wang, H Liu Advances in Neural Information Processing Systems 28, 2015 | 178* | 2015 |
| BOND: Bert-assisted open-domain named entity recognition with distant supervision C Liang, Y Yu, H Jiang, S Er, R Wang, T Zhao, C Zhang Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 152 | 2020 |
| Automated diagnoses of attention deficit hyperactive disorder using magnetic resonance imaging A Eloyan, J Muschelli, MB Nebel, H Liu, F Han, T Zhao, AD Barber, S Joel, ... Frontiers in systems neuroscience 6, 61, 2012 | 141 | 2012 |
| Transformer hawkes process S Zuo, H Jiang, Z Li, T Zhao, H Zha International conference on machine learning, 11692-11702, 2020 | 129 | 2020 |
| Deep hyperspherical learning W Liu, YM Zhang, X Li, Z Yu, B Dai, T Zhao, L Song Advances in neural information processing systems 30, 2017 | 126 | 2017 |
| The flare package for high dimensional linear regression and precision matrix estimation in R X Li, T Zhao, X Yuan, H Liu Journal of Machine Learning Research, 2015 | 107* | 2015 |
| Symmetry, saddle points, and global optimization landscape of nonconvex matrix factorization X Li, J Lu, R Arora, J Haupt, H Liu, Z Wang, T Zhao IEEE Transactions on Information Theory 65 (6), 3489-3514, 2019 | 96* | 2019 |
| Nonconvex sparse learning via stochastic optimization with progressive variance reduction X Li, R Arora, H Liu, J Haupt, T Zhao arXiv preprint arXiv:1605.02711 (ICML), 2016 | 96* | 2016 |
| Efficient approximation of deep relu networks for functions on low dimensional manifolds M Chen, H Jiang, W Liao, T Zhao Advances in neural information processing systems 32, 2019 | 79 | 2019 |
| Calibrated multivariate regression with application to neural semantic basis discovery H Liu, L Wang, T Zhao Journal of Machine Learning Research, 2015 | 75* | 2015 |
| Accelerated mini-batch randomized block coordinate descent method T Zhao, M Yu, Y Wang, R Arora, H Liu Advances in neural information processing systems 27, 2014 | 75 | 2014 |
| Sparse covariance matrix estimation with eigenvalue constraints H Liu, L Wang, T Zhao Journal of Computational and Graphical Statistics 23 (2), 439-459, 2014 | 73 | 2014 |
| CODA: High dimensional copula discriminant analysis F Han, T Zhao, H Liu Journal of Machine Learning Research, 2013 | 70 | 2013 |
| On tighter generalization bound for deep neural networks: Cnns, resnets, and beyond X Li, J Lu, Z Wang, J Haupt, T Zhao arXiv preprint arXiv:1806.05159, 2018 | 67 | 2018 |
| Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks?---A Neural Tangent Kernel Perspective K Huang, Y Wang, M Tao, T Zhao Advances in neural information processing systems 33, 2698-2709, 2020 | 66 | 2020 |
| Fine-tuning pre-trained language model with weak supervision: A contrastive-regularized self-training approach Y Yu, S Zuo, H Jiang, W Ren, T Zhao, C Zhang arXiv preprint arXiv:2010.07835 (NAACL), 2020 | 62 | 2020 |
| Pathwise coordinate optimization for sparse learning: Algorithm and theory T Zhao, H Liu, T Zhang The Annals of Statistics 46 (1), 180-218, 2018 | 59* | 2018 |
