プライベートの勉強会の準備資料(備忘)
■ Causal forests
[メイン論文] Stefan Wager, Susan Athey.(2018), "Estimation and Inference of Heterogeneous Treatment Effects using Random Forests",Journal of the American Statistical Association.
https://www.gsb.stanford.edu/faculty-research/publications/estimation-inference-heterogeneous-treatment-effects-using-random
[サブ論文]Athey, S., and Imbens, G. (2016), “Recursive Partitioning for Heterogeneous Causal Effects,” Proceedings of the National Academy of Sciences.
https://www.pnas.org/content/pnas/113/27/7353.full.pdf
■ R-Learner?
[論文]Xinkun Nie, Stefan Wager.(2018), "Quasi-Oracle Estimation of Heterogeneous Treatment Effects", Atlantic Causal Inference Conference.
https://arxiv.org/pdf/1712.04912v3.pdf
■ 事例論文
[紹介論文]
"Improve User Retention with Causal Learning" [Uber, KDD2019]
http://proceedings.mlr.press/v104/du19a/du19a.pdf