Implementing Sub-Gaussian IPW and DR #149
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Co-authored-by: yuta-saito <32621707+usaito@users.noreply.github.com>
…importance weight estimator
apply 2nd review Co-authored-by: yuta-saito <32621707+usaito@users.noreply.github.com>
[Review] Feature: Balanced-OPE estimators
usaito
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Overview
obp.ope.SubGaussianInverseProbabilityWeightingandobp.ope.SubGaussianDoublyRobust. Specifically, these estimators use the weight transformation stated in Definition 4.1 with "s=1". Users can specify value of lambda (hyperparameter of the estimators).References
Alberto Maria Metelli, Alessio Russo, and Marcello Restelli.
"Subgaussian and Differentiable Importance Sampling for Off-Policy Evaluation and Learning.", NeurIPS2021.
https://proceedings.neurips.cc/paper/2021/hash/4476b929e30dd0c4e8bdbcc82c6ba23a-Abstract.html
Philip S. Thomas, Georgios Theocharous, and Mohammad Ghavamzadeh.
"High Confidence Off-Policy Evaluation" AAAI2015.
https://www.cs.utexas.edu/~sniekum/classes/RLFD-F17/papers/Thomas2015.pdf