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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 1–50 of 265 papers

TitleStatusHype
Off-Policy Evaluation for Large Action Spaces via EmbeddingsCode2
Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior ModelCode2
Evaluating the Robustness of Off-Policy EvaluationCode1
COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction EstimationCode1
Anytime-valid off-policy inference for contextual banditsCode1
BCORLE(): An Offline Reinforcement Learning and Evaluation Framework for Coupons Allocation in E-commerce MarketCode1
Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy EvaluationCode1
Doubly Robust Distributionally Robust Off-Policy Evaluation and LearningCode1
Unifying Gradient Estimators for Meta-Reinforcement Learning via Off-Policy EvaluationCode1
Off-Policy Evaluation via Adaptive Weighting with Data from Contextual BanditsCode1
Benchmarks for Deep Off-Policy EvaluationCode1
A Policy-Guided Imitation Approach for Offline Reinforcement LearningCode1
Offline RL Without Off-Policy EvaluationCode1
A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor RepresentationCode1
Trajectory World Models for Heterogeneous EnvironmentsCode1
Model Selection for Offline Reinforcement Learning: Practical Considerations for Healthcare SettingsCode1
Off-Policy Evaluation of Ranking Policies under Diverse User BehaviorCode1
SCOPE-RL: A Python Library for Offline Reinforcement Learning and Off-Policy EvaluationCode1
Open Bandit Dataset and Pipeline: Towards Realistic and Reproducible Off-Policy EvaluationCode1
Counterfactual Evaluation of Slate Recommendations with Sequential Reward InteractionsCode1
Active Offline Policy SelectionCode1
Optimal Off-Policy Evaluation from Multiple Logging PoliciesCode1
Bayesian Off-Policy Evaluation and Learning for Large Action Spaces—0
Adaptive Trade-Offs in Off-Policy Learning—0
Debiasing Samples from Online Learning Using Bootstrap—0
Balancing Immediate Revenue and Future Off-Policy Evaluation in Coupon Allocation—0
An Instrumental Variable Approach to Confounded Off-Policy Evaluation—0
Bayesian Counterfactual Mean Embeddings and Off-Policy Evaluation—0
Data-Driven Off-Policy Estimator Selection: An Application in User Marketing on An Online Content Delivery Service—0
Accountable Off-Policy Evaluation via a Kernelized Bellman Statistics—0
Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization—0
Counterfactual Learning with General Data-generating Policies—0
Data Poisoning Attacks on Off-Policy Policy Evaluation Methods—0
Deep Jump Q-Evaluation for Offline Policy Evaluation in Continuous Action Space—0
A maximum-entropy approach to off-policy evaluation in average-reward MDPs—0
A Unified Off-Policy Evaluation Approach for General Value Function—0
Accelerating Offline Reinforcement Learning Application in Real-Time Bidding and Recommendation: Potential Use of Simulation—0
Combining Parametric and Nonparametric Models for Off-Policy Evaluation—0
A Fast Convergence Theory for Offline Decision Making—0
CoinDICE: Off-Policy Confidence Interval Estimation—0
Characterization of Efficient Influence Function for Off-Policy Evaluation Under Optimal Policies—0
Concept-driven Off Policy Evaluation—0
Confidence Interval for Off-Policy Evaluation from Dependent Samples via Bandit Algorithm: Approach from Standardized Martingales—0
Confident Natural Policy Gradient for Local Planning in q_π-realizable Constrained MDPs—0
Automated Off-Policy Estimator Selection via Supervised Learning—0
Conformal Off-Policy Evaluation in Markov Decision Processes—0
Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning—0
Conformal Off-Policy Prediction in Contextual Bandits—0
Confounding-Robust Policy Evaluation in Infinite-Horizon Reinforcement Learning—0
Causality and Batch Reinforcement Learning: Complementary Approaches To Planning In Unknown Domains—0
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