Semiparametric Off-Policy Inference for Optimal Policy Values under Possible Non-Uniqueness
Fuente:
arXiv
Enregistré dans:
| Auteur principal: | Wei, Haoyu |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
Inference on Optimal Policy Values and Other Irregular Functionals via Softmax Smoothing
par: Whitehouse, Justin, et autres
Publié: (2025)
par: Whitehouse, Justin, et autres
Publié: (2025)
Minimax Semiparametric Learning With Approximate Sparsity
par: Bradic, Jelena, et autres
Publié: (2019)
par: Bradic, Jelena, et autres
Publié: (2019)
Bayesian Semiparametric Causal Inference: Targeted Doubly Robust Estimation of Treatment Effects
par: Sert, Gözde, et autres
Publié: (2025)
par: Sert, Gözde, et autres
Publié: (2025)
Near-Optimal Non-Parametric Sequential Tests and Confidence Sequences with Possibly Dependent Observations
par: Bibaut, Aurelien, et autres
Publié: (2022)
par: Bibaut, Aurelien, et autres
Publié: (2022)
Policy Learning for Optimal Dynamic Treatment Regimes with Observational Data
par: Sakaguchi, Shosei
Publié: (2024)
par: Sakaguchi, Shosei
Publié: (2024)
Semiparametric inference for impulse response functions using double/debiased machine learning
par: Ballinari, Daniele, et autres
Publié: (2024)
par: Ballinari, Daniele, et autres
Publié: (2024)
Causal-Policy Forest for End-to-End Policy Learning
par: Kato, Masahiro
Publié: (2025)
par: Kato, Masahiro
Publié: (2025)
General Bayesian Policy Learning
par: Kato, Masahiro
Publié: (2026)
par: Kato, Masahiro
Publié: (2026)
Policy Learning with Distributional Welfare
par: Cui, Yifan, et autres
Publié: (2023)
par: Cui, Yifan, et autres
Publié: (2023)
Optimal Conditional Inference in Adaptive Experiments
par: Chen, Jiafeng, et autres
Publié: (2023)
par: Chen, Jiafeng, et autres
Publié: (2023)
Nonparametric Uniform Inference in Binary Classification and Policy Values
par: Liu, Nan, et autres
Publié: (2025)
par: Liu, Nan, et autres
Publié: (2025)
The Local Approach to Causal Inference under Network Interference
par: Auerbach, Eric, et autres
Publié: (2021)
par: Auerbach, Eric, et autres
Publié: (2021)
Entrywise Inference for Missing Panel Data: A Simple and Instance-Optimal Approach
par: Yan, Yuling, et autres
Publié: (2024)
par: Yan, Yuling, et autres
Publié: (2024)
ScoreMatchingRiesz: Score Matching for Debiased Machine Learning and Policy Path Estimation
par: Kato, Masahiro
Publié: (2025)
par: Kato, Masahiro
Publié: (2025)
Method-of-Moments Inference for GLMs and Doubly Robust Functionals under Proportional Asymptotics
par: Chen, Xingyu, et autres
Publié: (2024)
par: Chen, Xingyu, et autres
Publié: (2024)
Identification and Inference in Nonlinear Dynamic Network Models
par: Vallarino, Diego
Publié: (2026)
par: Vallarino, Diego
Publié: (2026)
Bridging the Gap between Empirical Welfare Maximization and Conditional Average Treatment Effect Estimation in Policy Learning
par: Kato, Masahiro
Publié: (2025)
par: Kato, Masahiro
Publié: (2025)
Beyond the Average: Distributional Causal Inference under Imperfect Compliance
par: Byambadalai, Undral, et autres
Publié: (2025)
par: Byambadalai, Undral, et autres
Publié: (2025)
Locally Regular and Efficient Tests in Non-Regular Semiparametric Models
par: Lee, Adam
Publié: (2024)
par: Lee, Adam
Publié: (2024)
On Efficient Estimation of Distributional Treatment Effects under Covariate-Adaptive Randomization
par: Byambadalai, Undral, et autres
Publié: (2025)
par: Byambadalai, Undral, et autres
Publié: (2025)
Robust Semiparametric Inference for Bayesian Additive Regression Trees
par: Breunig, Christoph, et autres
Publié: (2025)
par: Breunig, Christoph, et autres
Publié: (2025)
On the Lower Confidence Band for the Optimal Welfare in Policy Learning
par: Ponomarev, Kirill, et autres
Publié: (2024)
par: Ponomarev, Kirill, et autres
Publié: (2024)
Regularizing Fairness in Optimal Policy Learning with Distributional Targets
par: Kock, Anders Bredahl, et autres
Publié: (2024)
par: Kock, Anders Bredahl, et autres
Publié: (2024)
Demistifying Inference after Adaptive Experiments
par: Bibaut, Aurélien, et autres
Publié: (2024)
par: Bibaut, Aurélien, et autres
Publié: (2024)
Debiased Nonparametric Regression for Statistical Inference and Distributionally Robustness
par: Kato, Masahiro
Publié: (2024)
par: Kato, Masahiro
Publié: (2024)
Minimax and Bayes Optimal Best-Arm Identification
par: Kato, Masahiro
Publié: (2025)
par: Kato, Masahiro
Publié: (2025)
Bayesian Semi-supervised Inference via a Debiased Modeling Approach
par: Sert, Gözde, et autres
Publié: (2025)
par: Sert, Gözde, et autres
Publié: (2025)
Anytime-Valid Inference for Double/Debiased Machine Learning of Causal Parameters
par: Dalal, Abhinandan, et autres
Publié: (2024)
par: Dalal, Abhinandan, et autres
Publié: (2024)
Minimax and Bayes Optimal Adaptive Experimental Design for Treatment Choice
par: Kato, Masahiro
Publié: (2025)
par: Kato, Masahiro
Publié: (2025)
Minimax Optimal Simple Regret in Two-Armed Best-Arm Identification
par: Kato, Masahiro
Publié: (2024)
par: Kato, Masahiro
Publié: (2024)
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation
par: Jin, Jikai, et autres
Publié: (2024)
par: Jin, Jikai, et autres
Publié: (2024)
Semi-Supervised Treatment Effect Estimation with Unlabeled Covariates for Prediction-Powered Causal Inference
par: Kato, Masahiro
Publié: (2025)
par: Kato, Masahiro
Publié: (2025)
A Unified Theory for Causal Inference: Direct Debiased Machine Learning via Bregman-Riesz Regression
par: Kato, Masahiro
Publié: (2025)
par: Kato, Masahiro
Publié: (2025)
Nonparametric Instrumental Variable Analysis Without Structural Equations: Debiased Inference on Functionals of Inverse Problems with No Solutions
par: Shen, Zikai, et autres
Publié: (2026)
par: Shen, Zikai, et autres
Publié: (2026)
Worst-Case Optimal Multi-Armed Gaussian Best Arm Identification with a Fixed Budget
par: Kato, Masahiro
Publié: (2023)
par: Kato, Masahiro
Publié: (2023)
Locally Optimal Fixed-Budget Best Arm Identification in Two-Armed Gaussian Bandits with Unknown Variances
par: Kato, Masahiro
Publié: (2023)
par: Kato, Masahiro
Publié: (2023)
Dynamic treatment effects: high-dimensional inference under model misspecification
par: Zhang, Yuqian, et autres
Publié: (2021)
par: Zhang, Yuqian, et autres
Publié: (2021)
Semiparametric Conditional Factor Models in Asset Pricing
par: Chen, Qihui, et autres
Publié: (2021)
par: Chen, Qihui, et autres
Publié: (2021)
Regression Discontinuity Design with Distribution-Valued Outcomes
par: Van Dijcke, David
Publié: (2025)
par: Van Dijcke, David
Publié: (2025)
A Unified Framework for Debiased Machine Learning: Riesz Representer Fitting under Bregman Divergence
par: Kato, Masahiro
Publié: (2026)
par: Kato, Masahiro
Publié: (2026)
Documents similaires
-
Inference on Optimal Policy Values and Other Irregular Functionals via Softmax Smoothing
par: Whitehouse, Justin, et autres
Publié: (2025) -
Minimax Semiparametric Learning With Approximate Sparsity
par: Bradic, Jelena, et autres
Publié: (2019) -
Bayesian Semiparametric Causal Inference: Targeted Doubly Robust Estimation of Treatment Effects
par: Sert, Gözde, et autres
Publié: (2025) -
Near-Optimal Non-Parametric Sequential Tests and Confidence Sequences with Possibly Dependent Observations
par: Bibaut, Aurelien, et autres
Publié: (2022) -
Policy Learning for Optimal Dynamic Treatment Regimes with Observational Data
par: Sakaguchi, Shosei
Publié: (2024)