Persistence in high-dimensional linear predictor selection and the virtue of overparametrization E Greenshtein, YA Ritov Bernoulli 10 (6), 971-988, 2004 | 453 | 2004 |
Nonparametric empirical Bayes and compound decision approaches to estimation of a high-dimensional vector of normal means LD Brown, E Greenshtein The Annals of Statistics, 1685-1704, 2009 | 188 | 2009 |
Best subset selection, persistence in high-dimensional statistical learning and optimization under l1 constraint E Greenshtein | 130 | 2006 |
The Poisson compound decision problem revisited LD Brown, E Greenshtein, Y Ritov Journal of the American Statistical Association 108 (502), 741-749, 2013 | 51 | 2013 |
Application of Non Parametric Empirical Bayes Estimation to High Dimensional Classification. E Greenshtein, J Park Journal of Machine Learning Research 10 (7), 2009 | 39 | 2009 |
A dynamic‐programming approach to continuous‐review obsolescent inventory problems I David, E Greenshtein, A Mehrez Naval Research Logistics (NRL) 44 (8), 757-774, 1997 | 30 | 1997 |
Asymptotic efficiency of simple decisions for the compound decision problem E Greenshtein, Y Ritov Lecture Notes-Monograph Series, 266-275, 2009 | 27 | 2009 |
Sure independence screening for ultrahigh dimensional feature space Discussion P Bickel, P Buehlmann, Q Yao, R Samworth, P Hall, DM Titterington, ... Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2008 | 24 | 2008 |
Comparison of sequential experiments E Greenshtein The Annals of Statistics 24 (1), 436-448, 1996 | 22 | 1996 |
Double-stage inspection for screening multi-characteristic items E Greenshtein, G Rabinowitz IIE transactions 29 (12), 1057-1061, 1997 | 16 | 1997 |
Estimating the mean of high valued observations in high dimensions E Greenshtein, J Park, YA Ritov Journal of Statistical Theory and Practice 2 (3), 407-418, 2008 | 14 | 2008 |
Empirical Bayes in the presence of explanatory variables N Cohen, E Greenshtein, Y Ritov Statistica Sinica, 333-357, 2013 | 11 | 2013 |
Regularization through variable selection and conditional MLE with application to classification in high dimensions E Greenshtein, J Park, G Lebanon Journal of statistical planning and inference 139 (2), 385-395, 2009 | 10 | 2009 |
Application of non-parametric empirical bayes to treatment of non-response E Greenshtein, T Itskov Statistica Sinica 28 (4), 2189-2208, 2018 | 8 | 2018 |
Robust test for detecting a signal in a high dimensional sparse normal vector E Greenshtein, J Park Journal of Statistical Planning and Inference 142 (6), 1445-1456, 2012 | 8 | 2012 |
Optimal and myopic search in a binary random vector A Dor, E Greenshtein, E Korach Journal of applied probability 35 (2), 463-472, 1998 | 8 | 1998 |
Comment: Empirical Bayes, compound decisions and exchangeability E Greenshtein, Y Ritov | 7 | 2019 |
Statistical information and expected number of observations for sequential experiments E Greenshtein, E Torgersen Journal of statistical planning and inference 59 (2), 229-240, 1997 | 7 | 1997 |
Brownian analysis of a buffered-flow system in the face of sudden obsolescence I David, E Greenshtein Operations research letters 19 (1), 43-49, 1996 | 7 | 1996 |
Asymptotically minimax regret procedures in regression model selection and the magnitude of the dimension penalty A Goldenshluger, E Greenshtein The Annals of Statistics 28 (6), 1620-1637, 2000 | 5 | 2000 |