mlsanityData to 14 Oct 2026

Nearest Neighbor Matching as Least Squares Density Ratio Estimation and Riesz Regression

arXiv 2510.24433 ↗First posted 28 Oct 2025econ.EM cs.LG math.STcited by 7

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Abstract (arXiv)

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 matching is an instance of density-ratio estimation with their new density-ratio estimator. Chernozhukov et al. (2024) develops Riesz regression for automatic debiased machine learning, which directly estimates the Riesz representer (or equivalently, the bias-correction term) by minimizing the mean squared error. In this study, we first prove that the density-ratio estimation method proposed in Lin et al. (2023) is essentially equivalent to Least-Squares Importance Fitting (LSIF) proposed in Kanamori et al. (2009) for direct density-ratio estimation. Furthermore, we derive Riesz regression using the LSIF framework. Based on these results, we derive NN matching from Riesz regression. This study is based on our work Kato (2025a) and Kato (2025b).

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 7 of its 23 references that are in the map. First posted on arXiv 28 Oct 2025.

Builds on

7 of 23 references.

References · 7

  1. 2020Telescoping Density-Ratio Estimationcited by 108
  2. 2020Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimationcited by 45
  3. 2020Off-Policy Evaluation and Learning for External Validity under a Covariate Shiftcited by 26
  4. 2023Augmented balancing weights as linear regressioncited by 21
  5. 2023Automatic Debiased Machine Learning for Covariate Shiftscited by 16
  6. 2025Direct Bias-Correction Term Estimation for Average Treatment Effect Estimationcited by 9
  7. 2025Direct Debiased Machine Learning via Bregman Divergence Minimizationcited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 4; 2026: 3.

7 papers.

  1. 2025Riesz Regression As Direct Density Ratio Estimationcited by 3
  2. 2025A Unified Theory for Causal Inference: Direct Debiased Machine Learning via Bregman-Riesz Regressioncited by 2
  3. 2025Semi-Supervised Treatment Effect Estimation with Unlabeled Covariates for Prediction-Powered Causal Inferencecited by 1
  4. 2025Causal-Policy Forest for End-to-End Policy Learningcited by 0
  5. 2026genriesz: A Python Package for Automatic Debiased Machine Learning with Generalized Riesz Regressioncited by 0
  6. 2026Prediction-Powered Causal Inference by Automatic Debiased Machine Learning and Semi-Supervised Riesz Regressioncited by 0
  7. 2026Vector Search As Nearest Neighbor Matching: RAG-based Policy Learning in Causal Inferencecited by 0