CauseBox: A Causal Inference Toolbox for BenchmarkingTreatment Effect Estimators with Machine Learning Methods.
Paras Sheth|Ujun Jeong|Ruocheng Guo|Huan Liu|K. Selçuk Candan
| Anthology ID: | DBLP:conf/cikm/ShethJGLC21 |
|---|---|
| Volume: | CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1 - 5, 2021 |
| Year: | 2021 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 4789-4793 |
| URL: | https://doi.org/10.1145/3459637.3481974 |
| DOI: | https://doi.org/10.1145/3459637.3481974 |
| DBLP: | conf/cikm/ShethJGLC21 |
| BibTeX: |
@inproceedings{sheth-2021-causebox,
author = {Paras Sheth and
Ujun Jeong and
Ruocheng Guo and
Huan Liu and
K. Sel\c{c}uk Candan},
editor = {Gianluca Demartini and
Guido Zuccon and
J. Shane Culpepper and
Zi Huang and
Hanghang Tong},
title = {{CauseBox: A Causal Inference Toolbox for BenchmarkingTreatment Effect Estimators with Machine Learning Methods}},
booktitle = {{CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1 - 5, 2021}},
pages = {4789--4793},
publisher = {ACM},
year = {2021},
url = {https://doi.org/10.1145/3459637.3481974},
doi = {https://doi.org/10.1145/3459637.3481974}
}