Anytime-Valid Inference for Double/Debiased Machine Learning of Causal Parameters

18 August 2024

Papers citing "Anytime-Valid Inference for Double/Debiased Machine Learning of Causal Parameters"

9 / 9 papers shown

Title
Efficient Adaptive Experimentation with Non-Compliance Miruna Oprescu Brian M Cho Nathan Kallus 110 0 0 23 May 2025
Estimating Causal Effects with Double Machine Learning -- A Method Evaluation Jonathan Fuhr Philipp Berens Dominik Papies 27 6 0 21 Mar 2024
Forster-Warmuth Counterfactual Regression: A Unified Learning Approach Yachong Yang Arun K. Kuchibhotla E. T. Tchetgen 36 3 0 31 Jul 2023
A Theory on Adam Instability in Large-Scale Machine Learning Igor Molybog Peter Albert Moya Chen Zach DeVito David Esiobu ... Puxin Xu Yuchen Zhang Melanie Kambadur Stephen Roller Susan Zhang AI4CE 44 32 0 19 Apr 2023
Training Data Influence Analysis and Estimation: A Survey Zayd Hammoudeh Daniel Lowd TDI 49 91 0 09 Dec 2022
How to avoid machine learning pitfalls: a guide for academic researchers M. Lones VLM FaML OnRL 81 79 0 05 Aug 2021
Demystifying statistical learning based on efficient influence functions Oliver Hines O. Dukes Karla Diaz-Ordaz S. Vansteelandt TDI 116 116 0 01 Jul 2021
Cyclical Learning Rates for Training Neural Networks L. Smith ODL 123 2,515 0 03 Jun 2015
On the Complexity of Best Arm Identification in Multi-Armed Bandit Models E. Kaufmann Olivier Cappé Aurélien Garivier 112 1,021 0 16 Jul 2014