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2002.03478
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Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions
International Conference on Machine Learning (ICML), 2020
10 February 2020
Omer Gottesman
Joseph D. Futoma
Yao Liu
Soanli Parbhoo
Leo Anthony Celi
Emma Brunskill
Finale Doshi-Velez
OffRL
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Papers citing
"Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions"
35 / 35 papers shown
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Data Poisoning Attacks on Off-Policy Policy Evaluation Methods
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Min Chi
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Relative Sparsity for Medical Decision Problems
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The Health Gym: Synthetic Health-Related Datasets for the Development of Reinforcement Learning Algorithms
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Michael Böhm
Louisa R Jorm
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Generalizing Off-Policy Evaluation From a Causal Perspective For Sequential Decision-Making
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Synthetic Acute Hypotension and Sepsis Datasets Based on MIMIC-III and Published as Part of the Health Gym Project
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Mark Polizzotto
S. Finfer
Louisa R Jorm
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105
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Case-based off-policy policy evaluation using prototype learning
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Fredrik D. Johansson
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182
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State Relevance for Off-Policy Evaluation
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Omer Gottesman
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171
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Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators
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Finite-Sample Analysis of Off-Policy Natural Actor-Critic with Linear Function Approximation
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Finite-Sample Analysis of Off-Policy Natural Actor-Critic Algorithm
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Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs
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