Generalization error bounds of dynamic treatment regimes in penalized regression-based learning
type: Item
instance of: scholarly article
title: Generalization error bounds of dynamic treatment regimes in penalized regression-based learning
DOI: 10.1214/22-AOS2171
author: Eun Jeong Oh
author: Min Qian
author: Ying Kuen Cheung
published in: The Annals of Statistics
publication date: 2022-11-02T00:00:00Z
Mathematics Subject Classification ID: 62H99
Mathematics Subject Classification ID: 62J07
Mathematics Subject Classification ID: 62P10
zbMATH DE Number: 7610762
zbMATH Keywords: backward induction
zbMATH Keywords: personalized medicine
zbMATH Keywords: regression-based learning
zbMATH Keywords: treatment decision making
zbMATH Keywords: variable selection
describes a project that uses: ORL
MaRDI profile type: Publication
full work available at URL: 22-aos2171
OpenAlex ID: W4293483658
cites work: Statistical methods for dynamic treatment regimes. Reinforcement learning, causal inference, and personalized medicine
cites work: Sequential multiple assignment randomized trial (SMART) with adaptive randomization for quality improvement in depression treatment program
cites work: Constructing dynamic treatment regimes over indefinite time horizons
cites work: Robust Q-Learning
cites work: Sequential Advantage Selection for Optimal Treatment Regimes
cites work: Risk bounds for CART classifiers under a margin condition
cites work: Regret-Regression for Optimal Dynamic Treatment Regimes
cites work: Doubly robust estimation of optimal treatment regimes for survival data -- with application to an HIV/AIDS study
cites work: Entropy Learning for Dynamic Treatment Regimes
cites work: Tree-based methods for individualized treatment regimes
cites work: Dynamic treatment regimes: technical challenges and applications
cites work: Estimating Dynamic Treatment Regimes in Mobile Health Using V-Learning
cites work: Demystifying Optimal Dynamic Treatment Regimes
cites work: Optimal Dynamic Treatment Regimes
cites work: Q3093292
cites work: Marginal Mean Models for Dynamic Regimes
cites work: D-learning to estimate optimal individual treatment rules
cites work: Performance guarantees for individualized treatment rules
cites work: Q4381627
cites work: Optimal Structural Nested Models for Optimal Sequential Decisions
cites work: Learning customized and optimized lists of rules with mathematical programming
cites work: \(Q\)- and \(A\)-learning methods for estimating optimal dynamic treatment regimes
cites work: Robust learning for optimal treatment decision with NP-dimensionality
cites work: High-dimensional \(A\)-learning for optimal dynamic treatment regimes
cites work: Penalized Q-learning for dynamic treatment regimens
cites work: A Simple Method for Estimating Interactions Between a Treatment and a Large Number of Covariates
cites work: Regression Shrinkage and Selection via The Lasso: A Retrospective
cites work: Optimal aggregation of classifiers in statistical learning.
cites work: High-dimensional generalized linear models and the lasso
cites work: Doubly-robust dynamic treatment regimen estimation via weighted least squares
cites work: C-learning: A new classification framework to estimate optimal dynamic treatment regimes
cites work: Robust estimation of optimal dynamic treatment regimes for sequential treatment decisions
cites work: Using decision lists to construct interpretable and parsimonious treatment regimes
cites work: Interpretable Dynamic Treatment Regimes
cites work: Estimating Individualized Treatment Rules Using Outcome Weighted Learning
cites work: New Statistical Learning Methods for Estimating Optimal Dynamic Treatment Regimes
cites work: Reinforcement Learning Trees
cites work: Proper Inference for Value Function in High-Dimensional Q-Learning for Dynamic Treatment Regimes
cites work: The Adaptive Lasso and Its Oracle Properties
cites work: On the adaptive elastic net with a diverging number of parameters
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description: scientific article; zbMATH DE number 7610762