Cover Image

Adaptive debiased machine learning using data-driven model selection techniques

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	van der Laan, Lars, Carone, Marco, Luedtke, Alex, van der Laan, Mark
Format:	Preprint
Published:	2023
Subjects:	Methodology Statistics Theory Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Doubly robust inference via calibration
by: van der Laan, Lars, et al.
Published: (2024)

Combining T-learning and DR-learning: a framework for oracle-efficient estimation of causal contrasts
by: van der Laan, Lars, et al.
Published: (2024)

Automatic Debiased Machine Learning for Smooth Functionals of Nonparametric M-Estimands
by: van der Laan, Lars, et al.
Published: (2025)

Stabilized Inverse Probability Weighting via Isotonic Calibration
by: van der Laan, Lars, et al.
Published: (2024)

Nonparametric Instrumental Variable Inference with Many Weak Instruments
by: van der Laan, Lars, et al.
Published: (2025)

A Researcher's Guide to Empirical Risk Minimization
by: van der Laan, Lars
Published: (2026)

Adaptive Targeted Maximum Likelihood Estimation of the Mean Potential Outcome under a Treatment Rule
by: Xu, Yichen, et al.
Published: (2026)

Adaptive-TMLE for the Average Treatment Effect based on Randomized Controlled Trial Augmented with Real-World Data
by: van der Laan, Mark, et al.
Published: (2024)

Score-Preserving Targeted Maximum Likelihood Estimation
by: Pimentel, Noel, et al.
Published: (2025)

Conditional Distributional Treatment Effects: Doubly Robust Estimation and Testing
by: Jain, Saksham, et al.
Published: (2026)

Sinkhorn Treatment Effects: A Causal Optimal Transport Measure
by: Agarwal, Medha, et al.
Published: (2026)

Propensity Score Augmentation in Matching-based Estimation of Causal Effects
by: Ulloa-Pérez, Ernesto, et al.
Published: (2024)

Calibeating Prediction-Powered Inference
by: van der Laan, Lars, et al.
Published: (2026)

Generalized Venn and Venn-Abers Calibration with Applications in Conformal Prediction
by: van der Laan, Lars, et al.
Published: (2025)

Efficient Inference for Inverse Reinforcement Learning and Dynamic Discrete Choice Models
by: van der Laan, Lars, et al.
Published: (2025)

HAL-MLE Log-Splines Density Estimation (Part I: Univariate)
by: Hou, Yilong, et al.
Published: (2026)

Self-Calibrating Conformal Prediction
by: van der Laan, Lars, et al.
Published: (2024)

Inference on Variable Importance for Treatment Effect Heterogeneity: Shapley Values and Beyond
by: Morzywolek, Pawel, et al.
Published: (2025)

Simplifying debiased inference via automatic differentiation and probabilistic programming
by: Luedtke, Alex
Published: (2024)

Machine learning to optimize precision in the analysis of randomized trials: A journey in pre-specified, yet data-adaptive learning
by: Balzer, Laura B., et al.
Published: (2025)

Towards a Unified Theory for Semiparametric Data Fusion with Individual-Level Data
by: Graham, Ellen, et al.
Published: (2024)

Hybrid Meta-learners for Estimating Heterogeneous Treatment Effects
by: Liang, Zhongyuan, et al.
Published: (2025)

Identifying and Estimating Causal Direct Effects Under Unmeasured Confounding
by: Boileau, Philippe, et al.
Published: (2026)

Statistical learning for constrained functional parameters in infinite-dimensional models
by: Nabi, Razieh, et al.
Published: (2024)

Debiased machine learning for counterfactual survival functionals based on left-truncated right-censored data
by: Morenz, Eric R., et al.
Published: (2024)

A general framework for inference on algorithm-agnostic variable importance
by: Williamson, Brian D., et al.
Published: (2020)

Estimation of causal dose-response functions under data fusion
by: Lim, Jaewon, et al.
Published: (2025)

Efficient Statistical Estimation for Sequential Adaptive Experiments with Implications for Adaptive Designs
by: Zhang, Wenxin, et al.
Published: (2025)

Semiparametric Double Reinforcement Learning with Applications to Long-Term Causal Inference
by: van der Laan, Lars, et al.
Published: (2025)

Semiparametric inference for impulse response functions using double/debiased machine learning
by: Ballinari, Daniele, et al.
Published: (2024)

Consistent model selection in the spiked Wigner model via AIC-type criteria
by: Mukherjee, Soumendu Sundar
Published: (2023)

Fuzzy Prediction Sets: Conformal Prediction with E-values
by: Koning, Nick W., et al.
Published: (2025)

Semi-Modular Inference: enhanced learning in multi-modular models by tempering the influence of components
by: Carmona, Chris U., et al.
Published: (2020)

Improving the Efficiency of Subgroup Analysis in Randomized Controlled Trials with TMLE
by: Qiu, Sky, et al.
Published: (2026)

Minimax optimal adaptive structured transfer learning through semi-parametric domain-varying coefficient model
by: Chen, Hanxiao, et al.
Published: (2026)

Finite sample-optimal adjustment sets in linear Gaussian causal models
by: Rutsch, Nadja, et al.
Published: (2025)

Model-based causal feature selection for general response types
by: Kook, Lucas, et al.
Published: (2023)

Causal inference via implied interventions
by: Meixide, Carlos García, et al.
Published: (2025)

Selective inference using randomized group lasso estimators for general models
by: Huang, Yiling, et al.
Published: (2023)

Efficient Targeted Maximum Likelihood Estimators for Two-Phase Design Problems
by: Qiu, Sky, et al.
Published: (2026)