Stefan Wager
Stefan Wager
Graduate School of Business, Stanford University
Verified email at - Homepage
Cited by
Cited by
Estimation and inference of heterogeneous treatment effects using random forests
S Wager, S Athey
Journal of the American Statistical Association 113 (523), 1228-1242, 2018
Generalized random forests
S Athey, J Tibshirani, S Wager
The Annals of Statistics 47 (2), 1148-1178, 2019
Dropout training as adaptive regularization
S Wager, S Wang, PS Liang
Advances in Neural Information Processing Systems, 351-359, 2013
Confidence intervals for random forests: The jackknife and the infinitesimal jackknife
S Wager, T Hastie, B Efron
The Journal of Machine Learning Research 15 (1), 1625-1651, 2014
Approximate residual balancing: Debiased inference of average treatment effects in high dimensions
S Athey, GW Imbens, S Wager
Journal of the Royal Statistical Society Series B 80 (4), 597-623, 2018
Policy learning with observational data
S Athey, S Wager
Econometrica 89 (1), 133-161, 2021
Quasi-oracle estimation of heterogeneous treatment effects
X Nie, S Wager
Biometrika 108 (2), 299-319, 2021
Sequential selection procedures and false discovery rate control
MG G'Sell, S Wager, A Chouldechova, R Tibshirani
Journal of the Royal Statistical Society: Series B 78 (2), 423-444, 2016
High-dimensional asymptotics of prediction: Ridge regression and classification
E Dobriban, S Wager
The Annals of Statistics 46 (1), 247-279, 2018
Synthetic difference in differences
D Arkhangelsky, S Athey, DA Hirshberg, GW Imbens, S Wager
National Bureau of Economic Research, 2019
Estimating treatment effects with causal forests: An application
S Athey, S Wager
Observational Studies 5, 2019
Adaptive concentration of regression trees, with application to random forests
S Wager, G Walther
arXiv preprint arXiv:1503.06388, 2015
Valuing lead time
S De Treville, I Bicer, V Chavez-Demoulin, V Hagspiel, N Schürhoff, ...
Journal of Operations Management 32 (6), 337-346, 2014
Estimating average treatment effects: Supplementary analyses and remaining challenges
S Athey, G Imbens, T Pham, S Wager
American Economic Review 107 (5), 278-81, 2017
High-dimensional regression adjustments in randomized experiments
S Wager, W Du, J Taylor, RJ Tibshirani
Proceedings of the National Academy of Sciences 113 (45), 12673-12678, 2016
Memory, communication, and statistical queries
J Steinhardt, G Valiant, S Wager
29th Annual Conference on Learning Theory, 1490–1516, 2016
Offline multi-action policy learning: Generalization and optimization
Z Zhou, S Athey, S Wager
arXiv preprint arXiv:1810.04778, 2018
Augmented minimax linear estimation
DA Hirshberg, S Wager
arXiv preprint arXiv:1712.00038, 2017
Optimized regression discontinuity designs
G Imbens, S Wager
Review of Economics and Statistics 101 (2), 264-278, 2019
Altitude training: Strong bounds for single-layer dropout
S Wager, W Fithian, S Wang, PS Liang
Advances in Neural Information Processing Systems, 100-108, 2014
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