4 papers · 1 filter
Covariate Balancing and Riesz Regression Should Be Guided by the Neyman Orthogonal Score in Debiased Machine Learning
Masahiro Kato
This position paper argues that, in debiased machine learning, balancing functions should be derived from the Neyman orthogonal score, not chosen only as functions of covariates. C…
Conformal Prediction for Nonparametric Instrumental Regression
Masahiro Kato
We propose a method for constructing distribution-free prediction intervals in nonparametric instrumental variable regression (NPIV), with finite-sample coverage guarantees. Buildi…
Causal-Policy Forest for End-to-End Policy Learning
Masahiro Kato
This study proposes an end-to-end algorithm for policy learning in causal inference. We observe data consisting of covariates, treatment assignments, and outcomes, where only the o…
Direct Bias-Correction Term Estimation for Average Treatment Effect Estimation
Masahiro Kato
This study considers the estimation of the direct bias-correction term for estimating the average treatment effect (ATE). Let be the observations, w…