6 papers
Counterexamples and Sufficient Conditions: Comments on "Optimally-Transported Generalized Method of Moments"
Masahiro Kato
We comment on the optimally-transported generalized method of moments (OTGMM) estimator proposed by Schennach & Starck (2026a) and give counterexamples to Theorems 2-6 under their…
ScoreMatchingRiesz: Score Matching for Debiased Machine Learning and Policy Path Estimation
Masahiro Kato
We propose ScoreMatchingRiesz, a family of Riesz representer estimators based on score matching. The Riesz representer is a key nuisance component in debiased machine learning, ena…
Debiased Nonparametric Regression for Statistical Inference and Distributionally Robustness
Masahiro Kato
This study proposes a debiasing method for smooth nonparametric estimators. While machine learning techniques such as random forests and neural networks have demonstrated strong pr…
Debiased Regression for Root-N-Consistent Conditional Mean Estimation
Masahiro Kato
This study introduces a debiasing method for regression estimators, including high-dimensional and nonparametric regression estimators. For example, nonparametric regression method…
A Note on Doubly Robust Estimator in Regression Discontinuity Designs
Masahiro Kato
This note introduces a doubly robust (DR) estimator for regression discontinuity (RD) designs. RD designs provide a quasi-experimental framework for estimating treatment effects, w…
A Policy Gradient Primal-Dual Algorithm for Constrained MDPs with Uniform PAC Guarantees
Toshinori Kitamura, Tadashi Kozuno, Masahiro Kato +6
We study a primal-dual (PD) reinforcement learning (RL) algorithm for online constrained Markov decision processes (CMDPs). Despite its widespread practical use, the existing theor…