Debiased Machine Learning without Sample-Splitting for Stable Estimators

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Debiased Machine Learning without Sample-Splitting for Stable Estimators

3 June 2022

Vasilis Syrgkanis

Morgane Austern

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Papers citing "Debiased Machine Learning without Sample-Splitting for Stable Estimators"

12 / 12 papers shown

Title
Inference in Partially Linear Models under Dependent Data with Deep Neural Networks Chad Brown 107 0 0 29 Oct 2024
Automatic debiasing of neural networks via moment-constrained learning Christian L. Hines Oliver J. Hines CML OOD 158 0 0 29 Sep 2024
FairViT: Fair Vision Transformer via Adaptive Masking Bowei Tian Ruijie Du Yanning Shen 64 1 0 20 Jul 2024
Is Cross-Validation the Gold Standard to Evaluate Model Performance? Garud Iyengar Henry Lam Tianyu Wang 86 0 0 03 Jul 2024
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation Jikai Jin Vasilis Syrgkanis CML 213 1 0 22 Feb 2024
RoME: A Robust Mixed-Effects Bandit Algorithm for Optimizing Mobile Health Interventions Easton K. Huch Jieru Shi Madeline R Abbott J. Golbus Alexander Moreno Walter Dempsey OffRL 55 0 0 11 Dec 2023
A Meta-Learning Method for Estimation of Causal Excursion Effects to Assess Time-Varying Moderation Jieru Shi Walter Dempsey CML 49 4 0 28 Jun 2023
Maximally Machine-Learnable Portfolios Philippe Goulet Coulombe Maximilian Göbel 85 3 0 08 Jun 2023
Robust Fitted-Q-Evaluation and Iteration under Sequentially Exogenous Unobserved Confounders David Bruns-Smith Angela Zhou OffRL 56 10 0 01 Feb 2023
Bagging Provides Assumption-free Stability Jake A. Soloff Rina Foygel Barber Rebecca Willett 69 11 0 30 Jan 2023
Nonparametric Estimation of Conditional Incremental Effects Alec McClean Zach Branson Edward H. Kennedy CML 60 8 0 07 Dec 2022
RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests Victor Chernozhukov Whitney Newey Victor Quintas-Martinez Vasilis Syrgkanis CML 105 40 0 06 Oct 2021