4 papers
Deconfounding Scores and Representation Learning for Causal Effect Estimation with Weak Overlap
Oscar Clivio, Alexander D'Amour, Alexander Franks +3
Overlap, also known as positivity, is a key condition for causal treatment effect estimation. Many popular estimators suffer from high variance and become brittle when features dif…
Two Approaches to Direct Estimation of Riesz Representers
David Bruns-Smith
The Riesz representer is a central object in semiparametric statistics and debiased/doubly-robust estimation. Two literatures in econometrics have highlighted the role for directly…
Ridge Boosting is Both Robust and Efficient
David Bruns-Smith, Zhongming Xie, Avi Feller
Estimators in statistics and machine learning must typically trade off between efficiency, having low variance for a fixed target, and distributional robustness, such as multiaccur…
Robust Fitted-Q-Evaluation and Iteration under Sequentially Exogenous Unobserved Confounders
David Bruns-Smith, Angela Zhou
Offline reinforcement learning is important in domains such as medicine, economics, and e-commerce where online experimentation is costly, dangerous or unethical, and where the tru…