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Found 4 papers, 3 papers with code
Semi-Parametric Efficient Policy Learning with Continuous Actions
Our results also apply if the model does not satisfy our semi-parametric form, but rather we measure regret in terms of the best projection of the true value function to this functional space.
Fisher-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India
We propose strategies to estimate and make inference on key features of heterogeneous effects in randomized experiments.
Double/Debiased/Neyman Machine Learning of Treatment Effects
A more general discussion and references to the existing literature are available in Chernozhukov, Chetverikov, Demirer, Duflo, Hansen, and Newey (2016).
Double/Debiased Machine Learning for Treatment and Causal Parameters
Fortunately, this regularization bias can be removed by solving auxiliary prediction problems via ML tools.
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