Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems.
Xuezhi Wang|Nithum Thain|Anu Sinha|Flavien Prost|Ed H. Chi|Jilin Chen|Alex Beutel
| Anthology ID: | DBLP:conf/wsdm/0002TSPCCB21 |
|---|---|
| Volume: | WSDM '21, The Fourteenth ACM International Conference on Web Search and Data Mining, Virtual Event, Israel, March 8-12, 2021 |
| Year: | 2021 |
| Venue: | Web Search and Data Mining (WSDM) |
| Publisher: | ACM |
| Pages: | 436-444 |
| URL: | https://doi.org/10.1145/3437963.3441732 |
| DOI: | https://doi.org/10.1145/3437963.3441732 |
| DBLP: | conf/wsdm/0002TSPCCB21 |
| BibTeX: |
@inproceedings{wang-2021-practical,
author = {Xuezhi Wang and
Nithum Thain and
Anu Sinha and
Flavien Prost and
Ed H. Chi and
Jilin Chen and
Alex Beutel},
editor = {Liane Lewin-Eytan and
David Carmel and
Elad Yom-Tov and
Eugene Agichtein and
Evgeniy Gabrilovich},
title = {{Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems}},
booktitle = {{WSDM '21, The Fourteenth ACM International Conference on Web Search and Data Mining, Virtual Event, Israel, March 8-12, 2021}},
pages = {436--444},
publisher = {ACM},
year = {2021},
url = {https://doi.org/10.1145/3437963.3441732},
doi = {https://doi.org/10.1145/3437963.3441732}
}