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Found 5 papers, 1 papers with code
Counterfactual Learning with General Data-generating Policies
Off-policy evaluation (OPE) attempts to predict the performance of counterfactual policies using log data from a different policy.
Optimal Decision Rules Under Partial Identification
I consider a class of statistical decision problems in which the policy maker must decide between two alternative policies to maximize social welfare based on a finite sample.
Algorithm as Experiment: Machine Learning, Market Design, and Policy Eligibility Rules
Algorithms make a growing portion of policy and business decisions.
Debiased Off-Policy Evaluation for Recommendation Systems
Efficient methods to evaluate new algorithms are critical for improving interactive bandit and reinforcement learning systems such as recommendation systems.
Efficient Counterfactual Learning from Bandit Feedback
What is the most statistically efficient way to do off-policy evaluation and optimization with batch data from bandit feedback?
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