17 citations · 60 across the 11 of their papers we have counts for
5 papers · 1 filter
Simulation-Based Inference for Adaptive Experiments
Brian M Cho, Aurélien Bibaut, Nathan Kallus
Multi-arm bandit experimental designs are increasingly being adopted over standard randomized trials due to their potential to improve outcomes for study participants, enable faste…
Nonparametric Instrumental Variable Inference with Many Weak Instruments
Lars van der Laan, Nathan Kallus, Aurélien Bibaut
We study inference on linear functionals in the nonparametric instrumental variable (NPIV) problem with a discretely-valued instrument under a many-weak-instruments asymptotic regi…
Evaluating Decision Rules Across Many Weak Experiments
Winston Chou, Colin Gray, Nathan Kallus +2
Technology firms conduct randomized controlled experiments ("A/B tests") to learn which actions to take to improve business outcomes. In firms with mature experimentation platforms…
Automatic Debiased Machine Learning for Smooth Functionals of Nonparametric M-Estimands
Lars van der Laan, Aurelien Bibaut, Nathan Kallus +1
We develop a unified framework for automatic debiased machine learning (autoDML) for inference on a broad class of statistical parameters. The framework applies to any smooth funct…
Demistifying Inference after Adaptive Experiments
Aurélien Bibaut, Nathan Kallus
Adaptive experiments such as multi-arm bandits adapt the treatment-allocation policy and/or the decision to stop the experiment to the data observed so far. This has the potential…