Perturbation Effect: A Metric to Counter Misleading Validation of Feature Attribution.
Ilija Simic|Vedran Sabol|Eduardo E. Veas
| Anthology ID: | DBLP:conf/cikm/SimicSV22 |
|---|---|
| Volume: | Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022 |
| Year: | 2022 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 1798-1807 |
| URL: | https://doi.org/10.1145/3511808.3557418 |
| DOI: | https://doi.org/10.1145/3511808.3557418 |
| DBLP: | conf/cikm/SimicSV22 |
| BibTeX: |
@inproceedings{simic-2022-perturbation,
author = {Ilija Simic and
Vedran Sabol and
Eduardo E. Veas},
editor = {Mohammad Al Hasan and
Li Xiong},
title = {{Perturbation Effect: A Metric to Counter Misleading Validation of Feature Attribution}},
booktitle = {{Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022}},
pages = {1798--1807},
publisher = {ACM},
year = {2022},
url = {https://doi.org/10.1145/3511808.3557418},
doi = {https://doi.org/10.1145/3511808.3557418}
}