Efficient augmentation and relaxation learning for individualized treatment rules using observational data

Ying-Qi Zhao, Eric B. Laber, Yang Ning, Sumona Saha, Bruce E. Sands. Efficient augmentation and relaxation learning for individualized treatment rules using observational data. Journal of Machine Learning Research, 20, 2019. [doi]

@article{ZhaoLNSS19,
  title = {Efficient augmentation and relaxation learning for individualized treatment rules using observational data},
  author = {Ying-Qi Zhao and Eric B. Laber and Yang Ning and Sumona Saha and Bruce E. Sands},
  year = {2019},
  url = {http://jmlr.org/papers/v20/18-191.html},
  researchr = {https://researchr.org/publication/ZhaoLNSS19},
  cites = {0},
  citedby = {0},
  journal = {Journal of Machine Learning Research},
  volume = {20},
}