On Robustness of Individualized Decision Rules
From MaRDI portal
Publication:6077600
DOI10.1080/01621459.2022.2038180arXiv1903.04367OpenAlexW4223497423MaRDI QIDQ6077600
Zhengling Qi, Jong-Shi Pang, Yu Feng Liu
Publication date: 18 October 2023
Published in: Journal of the American Statistical Association (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1903.04367
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- \(Q\)- and \(A\)-learning methods for estimating optimal dynamic treatment regimes
- Performance guarantees for individualized treatment rules
- Statistical treatment choice based on asymmetric minimax regret criteria
- Inferring welfare maximizing treatment assignment under budget constraints
- Fast rates for support vector machines using Gaussian kernels
- D-learning to estimate optimal individual treatment rules
- High-dimensional \(A\)-learning for optimal dynamic treatment regimes
- Tree based weighted learning for estimating individualized treatment rules with censored data
- Minimax regret treatment choice with finite samples
- Coherent Measures of Risk
- Using decision lists to construct interpretable and parsimonious treatment regimes
- The Oxford Handbook of Bayesian Econometrics
- Computing B-Stationary Points of Nonsmooth DC Programs
- Expected Utility, Penalty Functions, and Duality in Stochastic Nonlinear Programming
- Estimating individualized treatment rules for ordinal treatments
- Tree-based methods for individualized treatment regimes
- When is ATE enough? Risk aversion and inequality aversion in evaluating training programs
- Asymptotics for Statistical Treatment Rules
- Risk-Constrained Reinforcement Learning with Percentile Risk Criteria
- Quantile-Optimal Treatment Regimes
- Concordance-Assisted Learning for Estimating Optimal Individualized Treatment Regimes
- Who Should Be Treated? Empirical Welfare Maximization Methods for Treatment Choice
- Estimating Individualized Treatment Rules Using Outcome Weighted Learning
- Optimal Dynamic Treatment Regimes
- A Robust Method for Estimating Optimal Treatment Regimes
- A Simple Method for Estimating Interactions Between a Treatment and a Large Number of Covariates
- Multicategory Outcome Weighted Margin-based Learning for Estimating Individualized Treatment Rules
- Learning Optimal Distributionally Robust Individualized Treatment Rules
- Policy Learning With Observational Data
- Modern Nonconvex Nondifferentiable Optimization
- A Sparse Random Projection-Based Test for Overall Qualitative Treatment Effects
- Multi-Armed Angle-Based Direct Learning for Estimating Optimal Individualized Treatment Rules With Various Outcomes
- Estimation of Individualized Decision Rules Based on an Optimized Covariate-Dependent Equivalent of Random Outcomes
- Doubly robust learning for estimating individualized treatment with censored data
- Adaptive contrast weighted learning for multi‐stage multi‐treatment decision‐making
- The Theory of Statistical Decision