4 papers
GAAVI: Global Asymptotic Anytime Valid Inference for the Conditional Mean Function
Brian M Cho, Raaz Dwivedi, Nathan Kallus
Inference on the conditional mean function (CMF) is central to tasks from adaptive experimentation to optimal treatment assignment and algorithmic fairness auditing. In this work,…
Exploration in the Limit
Brian M. Cho, Nathan Kallus
In fixed-confidence best arm identification (BAI), the objective is to quickly identify the optimal option while controlling the probability of error below a desired threshold. Des…
Efficient Adaptive Experimentation with Noncompliance
Miruna Oprescu, Brian M Cho, Nathan Kallus
We study the problem of estimating the average treatment effect (ATE) in adaptive experiments where treatment can only be encouraged -- rather than directly assigned -- via a binar…
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…