This software package implements the multiply robust method proposed in the paper "Multiply Robust Estimation for Local Distribution Shifts with Multiple Domains".
@inproceedings{wilkins-reeves2024multiply,
author = {Wilkins-Reeves, Steven and Chen, Xu and Ma, Qi and Agarwal, Christine and Hofleitner, Aude},
title = {{Multiply Robust Estimation for Local Distribution Shifts with Multiple Domains}},
booktitle = {Proceedings of the 41st International Conference on Machine Learning. (ICML 2024)},
year = {2024},
}
- estimators: implement the multiply robust estimation method
- utils: implement utility functions including data preprocessing and segment clustering algorithms
- weights: implement different importance weighting methods to adjust for covariate shifts and label shifts
A demo notebook will be added!
Installation Requirements
- Python >= 3.6
- numpy >= 1.24.4
- sklearn >= 1.2.2
- xgboost >= 1.2.0
- scipy >= 1.10.1
- cvxopt >= 1.2.7
See the CONTRIBUTING file for how to help out.
multiply_robust package is MIT licensed, as found in the LICENSE file.