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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 101–150 of 265 papers

TitleStatusHype
A Review of Off-Policy Evaluation in Reinforcement Learning—0
Doubly Robust Kernel Statistics for Testing Distributional Treatment EffectsCode0
Low Variance Off-policy Evaluation with State-based Importance SamplingCode0
Counterfactual Learning with General Data-generating Policies—0
Offline Policy Evaluation and Optimization under Confounding—0
Policy-Adaptive Estimator Selection for Off-Policy EvaluationCode0
Counterfactual Learning with Multioutput Deep KernelsCode0
Bayesian Counterfactual Mean Embeddings and Off-Policy Evaluation—0
Beyond the Return: Off-policy Function Estimation under User-specified Error-measuring Distributions—0
Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous ActionsCode0
Anytime-valid off-policy inference for contextual banditsCode1
Off-policy evaluation for learning-to-rank via interpolating the item-position model and the position-based model—0
A Policy-Guided Imitation Approach for Offline Reinforcement LearningCode1
Off-Policy Evaluation for Episodic Partially Observable Markov Decision Processes under Non-Parametric Models—0
Towards Robust Off-Policy Evaluation via Human Inputs—0
Towards A Unified Policy Abstraction Theory and Representation Learning Approach in Markov Decision Processes—0
On the Reuse Bias in Off-Policy Reinforcement LearningCode0
Statistical Estimation of Confounded Linear MDPs: An Instrumental Variable Approach—0
Future-Dependent Value-Based Off-Policy Evaluation in POMDPsCode0
Conformal Off-policy PredictionCode0
Conformal Off-Policy Prediction in Contextual Bandits—0
Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks—0
Markovian Interference in Experiments—0
Hybrid Value Estimation for Off-policy Evaluation and Offline Reinforcement Learning—0
Counterfactual Analysis in Dynamic Latent State Models—0
COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction EstimationCode1
Scalable and Robust Self-Learning for Skill Routing in Large-Scale Conversational AI Systems—0
Off-Policy Evaluation with Online Adaptation for Robot Exploration in Challenging Environments—0
Model-Free and Model-Based Policy Evaluation when Causality is UncertainCode0
Marginalized Operators for Off-policy Reinforcement Learning—0
Bellman Residual Orthogonalization for Offline Reinforcement Learning—0
Off-Policy Evaluation in Embedded Spaces—0
Off-Policy Evaluation with Policy-Dependent Optimization Response—0
A Multi-Agent Reinforcement Learning Framework for Off-Policy Evaluation in Two-sided MarketsCode0
Doubly Robust Distributionally Robust Off-Policy Evaluation and LearningCode1
Off-Policy Evaluation for Large Action Spaces via EmbeddingsCode2
Off-Policy Fitted Q-Evaluation with Differentiable Function Approximators: Z-Estimation and Inference Theory—0
Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior ModelCode2
Generalizing Off-Policy Evaluation From a Causal Perspective For Sequential Decision-Making—0
On Well-posedness and Minimax Optimal Rates of Nonparametric Q-function Estimation in Off-policy Evaluation—0
Off-Policy Evaluation Using Information Borrowing and Context-Based SwitchingCode0
Optimal discharge of patients from intensive care via a data-driven policy learning framework—0
BCORLE(): An Offline Reinforcement Learning and Evaluation Framework for Coupons Allocation in E-commerce MarketCode1
Weighted model estimation for offline model-based reinforcement learning—0
Subgaussian and Differentiable Importance Sampling for Off-Policy Evaluation and LearningCode0
Loss Functions for Discrete Contextual Pricing with Observational Data—0
A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision ProcessesCode0
SOPE: Spectrum of Off-Policy EstimatorsCode0
Proximal Reinforcement Learning: Efficient Off-Policy Evaluation in Partially Observed Markov Decision ProcessesCode0
Towards Hyperparameter-free Policy Selection for Offline Reinforcement LearningCode0
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