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Causal inference has received great attention across different fields from economics, statistics, education, medicine, to machine learning.
Statistics and Causal Inference (with discussion)
Holland, Paul W · 1986
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Reinforcement learning: An introduction
Sutton, Richard S. and Barto, Andrew G · 1998
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Random Forests
Breiman, Leo · 2001
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Observational studies
Rosenbaum, Paul R · 2002
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Doubly robust estimation in missing data and causal inference models
Bang, Heejung and Robins, James M · 2005
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Domain adaptation for statistical classifiers
Daume III, Hal and Marcu, Daniel · 2006
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Data analysis using regression and multilevel/hierarchical models
Gelman, Andrew and Hill, Jennifer · 2006
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Demystifying double robustness: A comparison of alternative strategies for estimating a population mean from incomplete data
Kang, Joseph DY and Schafer, Joseph L · 2007
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Causal effect models for realistic individualized treatment and intention to treat rules
van der Laan, Mark J and Petersen, Maya L · 2007
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A literature survey on domain adaptation of statistical classifiers
Jiang, Jing · 2008
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Causality
Pearl, Judea · 2009
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Contextual bandit algorithms with supervised learning guarantees
Beygelzimer, Alina, Langford, John, Li, Lihong, Reyzin, Lev, and Schapire, Robert E · 2010
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Bart: Bayesian additive regression trees
Chipman, Hugh A, George, Edward I, and McCulloch, Robert E · 2010
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Learning from logged implicit exploration data
Strehl, Alex, Langford, John, Li, Lihong, and Kakade, Sham M · 2010
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An introduction to propensity score methods for reducing the effects of confounding in observational studies
Austin, Peter C · 2011
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Doubly robust policy evaluation and learning
Dudík, Miroslav, Langford, John, and Li, Lihong · 2011
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction
Hastie, Trevor, Tibshirani, Robert, and Friedman, Jerome · 2011
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Bayesian nonparametric modeling for causal inference
Counterfactuals and causal inference
Morgan, Stephen L and Winship, Christopher · 2014
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A simple method for estimating interactions between a treatment and a large number of covariates
Tian, Lu, Alizadeh, Ash A, Gentles, Andrew J, and Tibshirani, Robert · 2014
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Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction
Imbens, Guido and Rubin, Donald · 2015
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Doubly Robust Covariate Shift Correction
Reddi, Sashank J., Poczos, Barnabas, and Smola, Alex · 2015
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Stable weights that balance covariates for estimation with incomplete outcome data
Zubizarreta, José R · 2015
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Recursive partitioning for heterogeneous causal effects
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Hill, Jennifer L · 2011
Cited alongside, same era.
Doubly robust policy evaluation and learning
Langford, John, Li, Lihong, and Dudík, Miroslav · 2011
Cited alongside, same era.
Causal inference using potential outcomes
Rubin, Donald B · 2011
Cited alongside, same era.
On causal and anticausal learning
Schölkopf, B., Janzing, D., Peters, J., Sgouritsa, E., Zhang, K., and Mooij, J · 2012
Cited alongside, same era.
Counterfactual reasoning and learning systems: The example of computational advertising
Bottou, Léon, Peters, Jonas, Quinonero-Candela, Joaquin, Charles, Denis X, Chickering, D Max, Portugaly, Elon, Ray, Dipankar, Simard, Patrice, and Snelson, Ed · 2013
Cited alongside, same era.
Inference on counterfactual distributions
Chernozhukov, Victor, Fernández-Val, Iván, and Melly, Blaise · 2013
Cited alongside, same era.
Domain adaptation and sample bias correction theory and algorithm for regression
Cortes, Corinna and Mohri, Mehryar · 2014
Cited alongside, same era.
Athey, Susan and Imbens, Guido · 2016
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Approximate Residual Balancing: De-Biased Inference of Average Treatment Effects in High Dimensions
Athey, Susan, Imbens, Guido, and Wager, Stefan · 2016
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NPCI: Non-parametrics for causal inference
Dorie, Vincent · 2016
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Learning Representations for Counterfactual Inference
Johansson, Fredrik D, Shalit, Uri, and Sontag, David · 2016
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Estimation and inference of heterogeneous treatment effects using random forests
Wager, Stefan and Athey, Susan · 2016
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Estimating average treatment effects: Supplementary analyses and remaining challenges
Athey, Susan, Imbens, Guido, Pham, Thai, and Wager, Stefan · 2017
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BayesTree: Bayesian additive regression trees
Chipman, Hugh and McCulloch, Robert · 2017
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