Off-policy evaluation in infinite-horizon reinforcement learning with latent confounders
Off-policy evaluation (OPE) in reinforcement learning is an important problem in settings
where experimentation is limited, such as healthcare. But, in these very same settings …
where experimentation is limited, such as healthcare. But, in these very same settings …
[PDF][PDF] Off-policy Evaluation in Infinite-horizon Reinforcement Learning with Latent Confounders
A Bennett, N Kallus, L Li, A Mousavi - academia.edu
Off-policy evaluation (OPE) in reinforcement learning is an important problem in settings
where experimentation is limited, such as education and healthcare. But, in these very same …
where experimentation is limited, such as education and healthcare. But, in these very same …
Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders
A Bennett, N Kallus, L Li… - … Conference on Artificial …, 2021 - proceedings.mlr.press
Off-policy evaluation (OPE) in reinforcement learning is an important problem in settings
where experimentation is limited, such as healthcare. But, in these very same settings …
where experimentation is limited, such as healthcare. But, in these very same settings …
Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders
A Bennett, N Kallus, L Li, A Mousavi - arXiv preprint arXiv:2007.13893, 2020 - arxiv.org
Off-policy evaluation (OPE) in reinforcement learning is an important problem in settings
where experimentation is limited, such as education and healthcare. But, in these very same …
where experimentation is limited, such as education and healthcare. But, in these very same …
Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders
A Bennett, N Kallus, L Li, A Mousavi - arXiv e-prints, 2020 - ui.adsabs.harvard.edu
Off-policy evaluation (OPE) in reinforcement learning is an important problem in settings
where experimentation is limited, such as education and healthcare. But, in these very same …
where experimentation is limited, such as education and healthcare. But, in these very same …
[PDF][PDF] Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders
A Bennett, N Kallus, L Li, A Mousavi - Proceedings of The 24th …, 2021 - par.nsf.gov
Off-policy evaluation (OPE) in reinforcement learning is an important problem in settings
where experimentation is limited, such as education and healthcare. But, in these very same …
where experimentation is limited, such as education and healthcare. But, in these very same …