| Distributed testing and estimation under sparse high dimensional models H Battey, J Fan, H Liu, J Lu, Z Zhu Annals of statistics 46 (3), 1352, 2018 | 191 | 2018 |
| Provable sparse tensor decomposition WW Sun, J Lu, H Liu, G Cheng Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2017 | 146 | 2017 |
| Distributed estimation and inference with statistical guarantees H Battey, J Fan, H Liu, J Lu, Z Zhu arXiv preprint arXiv:1509.05457, 2015 | 92 | 2015 |
| Heteroskedastic and imbalanced deep learning with adaptive regularization K Cao, Y Chen, J Lu, N Arechiga, A Gaidon, T Ma arXiv preprint arXiv:2006.15766, 2020 | 69 | 2020 |
| 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 | 69 | 2018 |
| Symmetry, saddle points, and global geometry of nonconvex matrix factorization X Li, Z Wang, J Lu, R Arora, J Haupt, H Liu, T Zhao arXiv preprint arXiv:1612.09296 1, 5.1-7.1, 2016 | 60 | 2016 |
| 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 | 54 | 2019 |
| Traction bronchiectasis/bronchiolectasis is associated with interstitial lung abnormality mortality T Hida, M Nishino, T Hino, J Lu, RK Putman, EF Gudmundsson, T Araki, ... European journal of radiology 129, 109073, 2020 | 46 | 2020 |
| Clinical knowledge extraction via sparse embedding regression (KESER) with multi-center large scale electronic health record data C Hong, E Rush, M Liu, D Zhou, J Sun, A Sonabend, VM Castro, ... NPJ digital medicine 4 (1), 151, 2021 | 33 | 2021 |
| Combinatorial inference for graphical models M Neykov, J Lu, H Liu The Annals of Statistics 47 (2), 795-827, 2019 | 29 | 2019 |
| Progression of traction bronchiectasis/bronchiolectasis in interstitial lung abnormalities is associated with increased all-cause mortality: Age Gene/Environment Susceptibility … T Hino, T Hida, M Nishino, J Lu, RK Putman, EF Gudmundsson, A Hata, ... European Journal of Radiology Open 8, 100334, 2021 | 23 | 2021 |
| Kernel meets sieve: Post-regularization confidence bands for sparse additive model J Lu, M Kolar, H Liu Journal of the American Statistical Association 115 (532), 2084-2099, 2020 | 23 | 2020 |
| Post-regularization inference for time-varying nonparanormal graphical models J Lu, M Kolar, H Liu Journal of Machine Learning Research 18 (203), 1-78, 2018 | 23 | 2018 |
| Nonparametric heterogeneity testing for massive data J Lu, G Cheng, H Liu arXiv preprint arXiv:1601.06212, 2016 | 23 | 2016 |
| Expert-supervised reinforcement learning for offline policy learning and evaluation A Sonabend, J Lu, LA Celi, T Cai, P Szolovits Advances in Neural Information Processing Systems 33, 18967-18977, 2020 | 20 | 2020 |
| Robust scatter matrix estimation for high dimensional distributions with heavy tails F Han, J Lu, H Liu Technical report, Princeton University, 2014 | 20 | 2014 |
| Interstitial lung abnormalities in patients with stage I non-small cell lung cancer are associated with shorter overall survival: the Boston lung cancer study T Hida, A Hata, J Lu, VI Valtchinov, T Hino, M Nishino, H Honda, ... Cancer Imaging 21, 1-7, 2021 | 19 | 2021 |
| Lagrangian inference for ranking problems Y Liu, EX Fang, J Lu Operations research 71 (1), 202-223, 2023 | 15 | 2023 |
| Multiview incomplete knowledge graph integration with application to cross-institutional ehr data harmonization D Zhou, Z Gan, X Shi, A Patwari, E Rush, CL Bonzel, VA Panickan, ... Journal of Biomedical Informatics 133, 104147, 2022 | 15 | 2022 |
| Post-regularization inference for dynamic nonparanormal graphical models J Lu, M Kolar, H Liu arXiv preprint arXiv:1512.08298, 2015 | 14 | 2015 |
