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Off-policy evaluation

Off-policy Evaluation (OPE), or offline evaluation in general, evaluates the performance of hypothetical policies leveraging only offline log data. It is particularly useful in applications where the online interaction involves high stakes and expensive setting such as precision medicine and recommender systems.

Papers

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Showing 51–75 of 265 papers

TitleStatusHype
An Instrumental Variable Approach to Confounded Off-Policy Evaluation—0
CoinDICE: Off-Policy Confidence Interval Estimation—0
Counterfactual Analysis in Dynamic Latent State Models—0
Balancing Immediate Revenue and Future Off-Policy Evaluation in Coupon Allocation—0
Characterization of Efficient Influence Function for Off-Policy Evaluation Under Optimal Policies—0
Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning—0
Counterfactual Learning with General Data-generating Policies—0
Bayesian Counterfactual Mean Embeddings and Off-Policy Evaluation—0
Doubly-Robust Off-Policy Evaluation with Estimated Logging Policy—0
Bayesian Off-Policy Evaluation and Learning for Large Action Spaces—0
Causality and Batch Reinforcement Learning: Complementary Approaches To Planning In Unknown Domains—0
Data-Driven Off-Policy Estimator Selection: An Application in User Marketing on An Online Content Delivery Service—0
A Spectral Approach to Off-Policy Evaluation for POMDPs—0
A Review of Off-Policy Evaluation in Reinforcement Learning—0
Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation—0
Development and Validation of Heparin Dosing Policies Using an Offline Reinforcement Learning Algorithm—0
Designing an Interpretable Interface for Contextual Bandits—0
Accountable Off-Policy Evaluation With Kernel Bellman Statistics—0
Defining Admissible Rewards for High Confidence Policy Evaluation—0
Bootstrapping Fitted Q-Evaluation for Off-Policy Inference—0
Double/Debiased Machine Learning for Dynamic Treatment Effects via g-Estimation—0
A Principled Path to Fitted Distributional Evaluation—0
Discovering an Aid Policy to Minimize Student Evasion Using Offline Reinforcement Learning—0
CANDOR: Counterfactual ANnotated DOubly Robust Off-Policy Evaluation—0
Beyond the Return: Off-policy Function Estimation under User-specified Error-measuring Distributions—0
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