| Synaptic, transcriptional and chromatin genes disrupted in autism S De Rubeis, X He, AP Goldberg, CS Poultney, K Samocha, ... Nature 515 (7526), 209-215, 2014 | 2590 | 2014 |
| Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism AJ Willsey, SJ Sanders, M Li, S Dong, AT Tebbenkamp, RA Muhle, ... Cell 155 (5), 997-1007, 2013 | 916 | 2013 |
| Differential privacy and robust statistics C Dwork, J Lei Proceedings of the 41st annual ACM symposium on Theory of computing, 371-380, 2009 | 851 | 2009 |
| Consistency of Spectral Clustering in Stochastic Block Models J Lei, A Rinaldo Annals of Statistics 43 (1), 215-237, 2013 | 680 | 2013 |
| Distribution-free predictive inference for regression J Lei, M G’Sell, A Rinaldo, RJ Tibshirani, L Wasserman Journal of the American Statistical Association 113 (523), 1094-1111, 2018 | 627 | 2018 |
| Learning with differential privacy: stability, learnability and the sufficiency and necessity of ERM principle YX Wang, J Lei, SE Fienberg Journal of Machine Learning Research 17 (183), 1-40, 2016 | 374* | 2016 |
| The autism-associated chromatin modifier CHD8 regulates other autism risk genes during human neurodevelopment J Cotney, RA Muhle, SJ Sanders, L Liu, AJ Willsey, W Niu, W Liu, L Klei, ... Nature communications 6 (1), 1-11, 2015 | 336 | 2015 |
| Distribution‐free prediction bands for non‐parametric regression J Lei, L Wasserman Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2014 | 243 | 2014 |
| Minimax Sparse Principal Subspace Estimation in High Dimensions VQ Vu, J Lei Annals of Statistics 41 (6), 2905-2947, 2012 | 216 | 2012 |
| A goodness-of-fit test for stochastic block models J Lei The Annals of Statistics 44 (1), 401-424, 2016 | 205 | 2016 |
| Network cross-validation for determining the number of communities in network data K Chen, J Lei Journal of the American Statistical Association 113 (521), 241-251, 2018 | 197 | 2018 |
| Fantope Projection and Selection: A near-optimal convex relaxation of sparse PCA VQ Vu, J Cho, J Lei, K Rohe Advances in Neural Information Processing Systems, 2670-2678, 2013 | 192 | 2013 |
| Distribution-Free Prediction Sets J Lei, J Robins, L Wasserman Journal of the American Statistical Association 108 (501), 278-287, 2013 | 184 | 2013 |
| Differentially private m-estimators J Lei Advances in Neural Information Processing Systems, 361-369, 2011 | 146 | 2011 |
| Minimax rates of estimation for sparse pca in high dimensions VQ Vu, J Lei 15th International Conference on Artificial Intelligence and Statistics …, 2012 | 145 | 2012 |
| DAWN: A framework to identify autism genes and subnetworks using gene expression and genetics L Liu, J Lei, SJ Sanders, AJ Willsey, Y Kou, AE Cicek, L Klei, C Lu, X He, ... Molecular Autism 5 (1), 22, 2014 | 142 | 2014 |
| Least ambiguous set-valued classifiers with bounded error levels M Sadinle, J Lei, L Wasserman Journal of the American Statistical Association 114 (525), 223-234, 2018 | 134 | 2018 |
| Convergence and concentration of empirical measures under Wasserstein distance in unbounded functional spaces J Lei Bernoulli 26 (1), 767-798, 2020 | 110 | 2020 |
| Classification with confidence J Lei Biometrika 101 (4), 755-769, 2014 | 110 | 2014 |
| A conformal prediction approach to explore functional data J Lei, A Rinaldo, L Wasserman Annals of Mathematics and Artificial Intelligence 74 (1-2), 29-43, 2015 | 100 | 2015 |
Larry WassermanProfessor, Department of Statistics and Machine Learning Department, Carnegie Mellon UniversityΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα stat.cmu.edu
