4 papers · 1 filter
Vector Search As Nearest Neighbor Matching: RAG-based Policy Learning in Causal Inference
Masahiro Kato, Taka Kato
We propose one-step and two-step methods for policy learning with retrieval-augmented generation (RAG). We formulate RAG-based action selection under the potential outcome framewor…
Generalized Riesz Regression: A Unified Framework for Debiased Machine Learning with Riesz Representer Fitting under Bregman Divergence
Masahiro Kato
Estimating the Riesz representer is central to debiased machine learning, yet the generator and representer model determine which regression directions their first-order conditions…
Direct Debiased Machine Learning via Bregman Divergence Minimization
Masahiro Kato
We develop a direct debiased machine learning framework comprising Neyman targeted estimation and generalized Riesz regression. Our framework unifies Riesz regression for automatic…
Nearest Neighbor Matching as Least Squares Density Ratio Estimation and Riesz Regression
Masahiro Kato
This study proves that Nearest Neighbor (NN) matching can be interpreted as an instance of Riesz regression for automatic debiased machine learning. Lin et al. (2023) shows that NN…