Projected state-action balancing weights for offline reinforcement learning
From MaRDI portal
Publication:6183753
DOI10.1214/23-aos2302arXiv2109.04640MaRDI QIDQ6183753
Raymond K. W. Wong, Zhengling Qi, Jiayi Wang
Publication date: 4 January 2024
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2109.04640
Cites Work
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- Large Sample Properties of Generalized Method of Moments Estimators
- Dynamic treatment regimes: technical challenges and applications
- Demystifying double robustness: a comparison of alternative strategies for estimating a population mean from incomplete data
- Some new asymptotic theory for least squares series: pointwise and uniform results
- Regularized least-squares regression: learning from a sequence
- High-dimensional \(A\)-learning for optimal dynamic treatment regimes
- Optimal global rates of convergence for nonparametric regression
- A distribution-free theory of nonparametric regression
- Batch policy learning in average reward Markov decision processes
- Nonparametric estimation of an additive model with a link function
- Estimation of Regression Coefficients When Some Regressors Are Not Always Observed
- Marginal Mean Models for Dynamic Regimes
- Quantile-Optimal Treatment Regimes
- Optimal sup-norm rates and uniform inference on nonlinear functionals of nonparametric IV regression
- Optimal Dynamic Treatment Regimes
- Approximate Residual Balancing: Debiased Inference of Average Treatment Effects in High Dimensions
- Generalized Optimal Matching Methods for Causal Inference
- Efficiently Breaking the Curse of Horizon in Off-Policy Evaluation with Double Reinforcement Learning
- Estimating Dynamic Treatment Regimes in Mobile Health Using V-Learning
- Minimal dispersion approximately balancing weights: asymptotic properties and practical considerations
- New Statistical Learning Methods for Estimating Optimal Dynamic Treatment Regimes
- Globally Efficient Non-Parametric Inference of Average Treatment Effects by Empirical Balancing Calibration Weighting
- Kernel-based covariate functional balancing for observational studies
- Instrumental Variable Estimation of Nonparametric Models
- Covariate Balancing Propensity Score
- Off-Policy Estimation of Long-Term Average Outcomes With Applications to Mobile Health
- Personalized Policy Learning Using Longitudinal Mobile Health Data
