The paper develops set-valued policies and conformal policy learning methods that output treatment sets with marginal coverage guarantees for robust decision-making under uncertainty.
Generalized random forests
4 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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A placebo-anchored cross-fitted doubly robust estimator for heterogeneous treatment effects in meta-analysis under covariate shift that improves accuracy at small target sample sizes.
A penalized likelihood estimator for GEV parameters, weighted by generalized random forest weights, is introduced for extreme quantile regression to improve tail extrapolation and handle many predictors.
ADHD status carries a direct penalty of 0.67 points on high school STEM GPA, with 63% of the total disparity not explained by observed sociodemographic or academic factors.
citing papers explorer
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Set-Valued Policy Learning
The paper develops set-valued policies and conformal policy learning methods that output treatment sets with marginal coverage guarantees for robust decision-making under uncertainty.
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Transfer Learning for Meta-analysis Under Covariate Shift
A placebo-anchored cross-fitted doubly robust estimator for heterogeneous treatment effects in meta-analysis under covariate shift that improves accuracy at small target sample sizes.
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Penalized estimation of GEV parameters for extreme quantile regression
A penalized likelihood estimator for GEV parameters, weighted by generalized random forest weights, is introduced for extreme quantile regression to improve tail extrapolation and handle many predictors.
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Causal Fairness Analysis of ADHD Status and High School STEM Outcomes
ADHD status carries a direct penalty of 0.67 points on high school STEM GPA, with 63% of the total disparity not explained by observed sociodemographic or academic factors.