| Discussion: The Dantzig selector: statistical estimation when p is much larger than n T Cai, J Lv The Annals of Statistics 35, 2365-2369, 2007 | 4427* | 2007 |
| Sure independence screening for ultrahigh dimensional feature space (with discussion) J Fan, J Lv Journal of the Royal Statistical Society Series B 70, 849-911, 2008 | 3184 | 2008 |
| A selective overview of variable selection in high dimensional feature space J Fan, J Lv Statistica Sinica 20 (1), 101, 2010 | 1109 | 2010 |
| Panning for gold: 'model-X' knockoffs for high dimensional controlled variable selection EJ Candès, Y Fan, L Janson, J Lv Journal of the Royal Statistical Society Series B 80, 551-577, 2018 | 812 | 2018 |
| High dimensional covariance matrix estimation using a factor model J Fan, Y Fan, J Lv Journal of Econometrics 147 (1), 186-197, 2008 | 793 | 2008 |
| Nonconcave penalized likelihood with NP-dimensionality J Fan, J Lv IEEE Transactions on Information Theory 57 (8), 5467-5484, 2011 | 503 | 2011 |
| A unified approach to model selection and sparse recovery using regularized least squares J Lv, Y Fan The Annals of Statistics 37 (6A), 3498-3528, 2009 | 431 | 2009 |
| Sparse high dimensional models in economics J Fan, J Lv, L Qi Annual Review of Economics 3, 291-317, 2011 | 276 | 2011 |
| DASSO: connections between the Dantzig selector and lasso GM James, P Radchenko, J Lv Journal of the Royal Statistical Society Series B 71 (1), 127-142, 2009 | 222 | 2009 |
| Estimating and testing high-dimensional mediation effects in epigenetic studies H Zhang, Y Zheng, Z Zhang, T Gao, B Joyce, G Yoon, W Zhang, ... Bioinformatics 32, 3150-3154, 2016 | 172 | 2016 |
| DeepPINK: reproducible feature selection in deep neural networks Y Lu, Y Fan, J Lv, WS Noble Advances in Neural Information Processing Systems (NeurIPS 2018), 2018 | 171 | 2018 |
| Model selection principles in misspecified models J Lv, JS Liu Journal of the Royal Statistical Society Series B 76, 141-167, 2014 | 162 | 2014 |
| Neural substrates related to motor memory with multiple timescales in sensorimotor adaptation S Kim, K Ogawa, J Lv, N Schweighofer, H Imamizu PLOS Biology 13, e1002312, 2015 | 107 | 2015 |
| High-dimensional sparse additive hazards regression W Lin, J Lv Journal of the American Statistical Association 108, 247-264, 2013 | 92 | 2013 |
| High dimensional thresholded regression and shrinkage effect Z Zheng, Y Fan, J Lv Journal of the Royal Statistical Society Series B 76, 627-649, 2014 | 90 | 2014 |
| Interaction pursuit in high-dimensional multi-response regression via distance correlation Y Kong, D Li, Y Fan, J Lv The Annals of Statistics 45, 897-922, 2017 | 83 | 2017 |
| RANK: large-scale inference with graphical nonlinear knockoffs Y Fan, E Demirkaya, G Li, J Lv Journal of the American Statistical Association 115, 362-379, 2020 | 69 | 2020 |
| Discussion: A significance test for the Lasso J Lv, Z Zheng The Annals of Statistics 42, 493-500, 2014 | 62* | 2014 |
| Asymptotic equivalence of regularization methods in thresholded parameter space Y Fan, J Lv Journal of the American Statistical Association 108, 1044-1061, 2013 | 62 | 2013 |
| IPAD: stable interpretable forecasting with knockoffs inference Y Fan, J Lv, M Sharifvaghefi, Y Uematsu Journal of the American Statistical Association 115, 1822-1834, 2020 | 58 | 2020 |