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Semiparametric doubly robust targeted double machine learning: a review

arXiv 2203.06469 ↗First posted 12 Mar 2022stat.MEcited by 129

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Abstract (arXiv)

In this review we cover the basics of efficient nonparametric parameter estimation (also called functional estimation), with a focus on parameters that arise in causal inference problems. We review both efficiency bounds (i.e., what is the best possible performance for estimating a given parameter?) and the analysis of particular estimators (i.e., what is this estimator's error, and does it attain the efficiency bound?) under weak assumptions. We emphasize minimax-style efficiency bounds, worked examples, and practical shortcuts for easing derivations. We gloss over most technical details, in the interest of highlighting important concepts and providing intuition for main ideas.

Key facts. Cited by 129 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Mar 2022.

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Citing papers per year: 2022: 10; 2023: 25; 2024: 31; 2025: 23; 2026: 40.

129 papers.

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  1. 2022A Review of Off-Policy Evaluation in Reinforcement Learningcited by 92
  2. 2022Causal Structure Learning: a Combinatorial Perspectivecited by 46
  3. 2022Anytime-valid off-policy inference for contextual banditscited by 37
  4. 2023Diagnosing Model Performance Under Distribution Shiftcited by 37
  5. 2023Using Imperfect Surrogates for Downstream Inference: Design-based Supervised Learning for Social Science Applications of Large Language Modelscited by 37
  6. 2025Predictions as Surrogates: Revisiting Surrogate Outcomes in the Age of AIcited by 31
  7. 2023Sharp Bounds for Generalized Causal Sensitivity Analysiscited by 24
  8. 2022Normalizing Flows for Interventional Density Estimationcited by 21
  9. 2023Plug-in Performative Optimizationcited by 20
  10. 2022Robust and Agnostic Learning of Conditional Distributional Treatment Effectscited by 18
  11. 2022Estimating individual treatment effects under unobserved confounding using binary instrumentscited by 17
  12. 2024Semiparametric conformal predictioncited by 13
38 more
  1. 2023Robust Fitted-Q-Evaluation and Iteration under Sequentially Exogenous Unobserved Confounderscited by 12
  2. 2023The Fundamental Limits of Structure-Agnostic Functional Estimationcited by 12
  3. 2026EdgeBench: Unveiling Scaling Laws of Learning from Real-World Environmentscited by 12
  4. 2023Fair Off-Policy Learning from Observational Datacited by 11
  5. 2024Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environmentscited by 11
  6. 2023Counterfactual Prediction Under Outcome Measurement Errorcited by 10
  7. 2023An Efficient Doubly-Robust Test for the Kernel Treatment Effectcited by 10
  8. 2024Longitudinal Targeted Minimum Loss-based Estimation with Temporal-Difference Heterogeneous Transformercited by 10
  9. 2024Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learnercited by 10
  10. 2025Orthogonal Survival Learners for Estimating Heterogeneous Treatment Effects from Time-to-Event Datacited by 10
  11. 2023Evaluation of Active Feature Acquisition Methods for Time-varying Feature Settingscited by 9
  12. 2024Linear Contextual Bandits with Interferencecited by 7
  13. 2023Fair and Robust Estimation of Heterogeneous Treatment Effects for Policy Learningcited by 6
  14. 2023Positivity-free Policy Learning with Observational Datacited by 6
  15. 2024Auditing Fairness under Unobserved Confoundingcited by 6
  16. 2024Hierarchical and Density-based Causal Clusteringcited by 6
  17. 2022A New Central Limit Theorem for the Augmented IPW Estimator: Variance Inflation, Cross-Fit Covariance and Beyondcited by 5
  18. 2023Efficient and robust transfer learning of optimal individualized treatment regimes with right-censored survival datacited by 5
  19. 2023Doubly Robust Counterfactual Classificationcited by 5
  20. 2023Kernel Debiased Plug-in Estimation: Simultaneous, Automated Debiasing without Influence Functions for Many Target Parameterscited by 5
  21. 2024A hierarchical decomposition for explaining ML performance discrepanciescited by 5
  22. 2024Semi-Supervised U-statisticscited by 5
  23. 2024Orthogonal Causal Calibrationcited by 5
  24. 2024Evaluating Model Performance Under Worst-case Subpopulationscited by 5
  25. 2024Prediction-Guided Active Experimentscited by 5
  26. 2025Efficient and Sharp Off-Policy Learning under Unobserved Confoundingcited by 5
  27. 2025Differentially Private Learners for Heterogeneous Treatment Effectscited by 5
  28. 2023Evaluation of Active Feature Acquisition Methods for Static Feature Settingscited by 4
  29. 2024Automated Efficient Estimation using Monte Carlo Efficient Influence Functionscited by 4
  30. 2024Improving the Finite Sample Estimation of Average Treatment Effects using Double/Debiased Machine Learning with Propensity Score Calibrationcited by 4
  31. 2024Estimating Wage Disparities Using Foundation Modelscited by 4
  32. 2024Comparing Targeting Strategies for Maximizing Social Welfare with Limited Resourcescited by 4
  33. 2025Double Machine Learning for Causal Inference under Shared-State Interferencecited by 4
  34. 2023The Connection Between R-Learning and Inverse-Variance Weighting for Estimation of Heterogeneous Treatment Effectscited by 3
  35. 2024Causal K-Means Clusteringcited by 3
  36. 2025Doubly-Robust Estimation of Counterfactual Policy Mean Embeddingscited by 3
  37. 2025Overlap-weighted orthogonal meta-learner for treatment effect estimation over timecited by 3
  38. 2026Topological Causal Effectscited by 3

50 most cited of 129 All 129 (JSON)