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Diffusion Asymptotics for Sequential Experiments


Feb 10, 2021
Stefan Wager, Kuang Xu


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Estimating heterogeneous treatment effects with right-censored data via causal survival forests


Jan 27, 2020
Yifan Cui, Michael R. Kosorok, Stefan Wager, Ruoqing Zhu


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Confidence Intervals for Policy Evaluation in Adaptive Experiments


Nov 07, 2019
Vitor Hadad, David A. Hirshberg, Ruohan Zhan, Stefan Wager, Susan Athey


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Smoothness-Adaptive Stochastic Bandits


Oct 22, 2019
Yonatan Gur, Ahmadreza Momeni, Stefan Wager


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Sufficient Representations for Categorical Variables


Aug 26, 2019
Jonathan Johannemann, Vitor Hadad, Susan Athey, Stefan Wager


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Covariate-Powered Empirical Bayes Estimation


Jun 04, 2019
Nikolaos Ignatiadis, Stefan Wager


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Learning When-to-Treat Policies


May 23, 2019
Xinkun Nie, Emma Brunskill, Stefan Wager


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Offline Multi-Action Policy Learning: Generalization and Optimization


Oct 10, 2018
Zhengyuan Zhou, Susan Athey, Stefan Wager


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Efficient Policy Learning


Oct 09, 2018
Susan Athey, Stefan Wager

* Results extended to cover interventions on endogenous or continuous treatments 

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Local Linear Forests


Jul 30, 2018
Rina Friedberg, Julie Tibshirani, Susan Athey, Stefan Wager


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Quasi-Oracle Estimation of Heterogeneous Treatment Effects


Jun 25, 2018
Xinkun Nie, Stefan Wager


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Generalized Random Forests


Apr 05, 2018
Susan Athey, Julie Tibshirani, Stefan Wager

* Forthcoming in the Annals of Statistics 

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Estimation and Inference of Heterogeneous Treatment Effects using Random Forests


Jul 10, 2017
Stefan Wager, Susan Athey

* To appear in the Journal of the American Statistical Association. Part of the results developed in this paper were made available as an earlier technical report "Asymptotic Theory for Random Forests", available at (arXiv:1405.0352) 

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High-dimensional regression adjustments in randomized experiments


Oct 27, 2016
Stefan Wager, Wenfei Du, Jonathan Taylor, Robert Tibshirani

* To appear in the Proceedings of the National Academy of Sciences. The present draft does not reflect final copyediting by the PNAS staff 

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Bootstrap-Based Regularization for Low-Rank Matrix Estimation


Jun 28, 2016
Julie Josse, Stefan Wager

* To appear in the Journal of Machine Learning Research 

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Asymptotic Theory for Random Forests


May 04, 2016
Stefan Wager

* This manuscript is superseded by "Estimation and Inference of Heterogeneous Treatment Effects using Random Forests" by Wager and Athey (arXiv:1510.04342). The new paper extends the asymptotic theory developed here, and applies it to causal inference in the potential outcomes framework with unconfoundedness. The present version is maintained online for archival purposes only 

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Adaptive Concentration of Regression Trees, with Application to Random Forests


Apr 30, 2016
Stefan Wager, Guenther Walther


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Data Augmentation via Levy Processes


Mar 21, 2016
Stefan Wager, William Fithian, Percy Liang


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High-Dimensional Asymptotics of Prediction: Ridge Regression and Classification


Nov 04, 2015
Edgar Dobriban, Stefan Wager

* Added a section on prediction versus estimation for ridge regression. Rewrote introduction. Other results unchanged 

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Weakly supervised clustering: Learning fine-grained signals from coarse labels


Sep 15, 2015
Stefan Wager, Alexander Blocker, Niall Cardin

* Annals of Applied Statistics 2015, Vol. 9, No. 2, 801-820 
* Published at http://dx.doi.org/10.1214/15-AOAS812 in the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

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The Statistics of Streaming Sparse Regression


Dec 13, 2014
Jacob Steinhardt, Stefan Wager, Percy Liang


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Feedback Detection for Live Predictors


Nov 01, 2014
Stefan Wager, Nick Chamandy, Omkar Muralidharan, Amir Najmi

* Advances in Neural Information Processing Systems (NIPS), 2014 

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Altitude Training: Strong Bounds for Single-Layer Dropout


Oct 31, 2014
Stefan Wager, William Fithian, Sida Wang, Percy Liang

* Advances in Neural Information Processing Systems (NIPS), 2014 

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Confidence Intervals for Random Forests: The Jackknife and the Infinitesimal Jackknife


Mar 29, 2014
Stefan Wager, Trevor Hastie, Bradley Efron

* To appear in Journal of Machine Learning Research (JMLR) 

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Dropout Training as Adaptive Regularization


Nov 01, 2013
Stefan Wager, Sida Wang, Percy Liang

* 11 pages. Advances in Neural Information Processing Systems (NIPS), 2013 

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