Pareto Solutions vs Dataset Optima: Concepts and Methods for Optimizing Competing Objectives with Constraints in Retrieval.
Soumyajit Gupta|Gurpreet Singh|Anubrata Das|Matthew Lease
| Anthology ID: | DBLP:conf/ictir/GuptaS0L21 |
|---|---|
| Volume: | ICTIR '21: The 2021 ACM SIGIR International Conference on the Theory of Information Retrieval, Virtual Event, Canada, July 11, 2021 |
| Year: | 2021 |
| Venue: | International Conference on the Theory of Information Retrieval (ICTIR) |
| Publisher: | ACM |
| Pages: | 43-52 |
| URL: | https://doi.org/10.1145/3471158.3472248 |
| DOI: | https://doi.org/10.1145/3471158.3472248 |
| DBLP: | conf/ictir/GuptaS0L21 |
| BibTeX: |
@inproceedings{gupta-2021-pareto,
author = {Soumyajit Gupta and
Gurpreet Singh and
Anubrata Das and
Matthew Lease},
editor = {Faegheh Hasibi and
Yi Fang and
Akiko Aizawa},
title = {{Pareto Solutions vs Dataset Optima: Concepts and Methods for Optimizing Competing Objectives with Constraints in Retrieval}},
booktitle = {{ICTIR '21: The 2021 ACM SIGIR International Conference on the Theory of Information Retrieval, Virtual Event, Canada, July 11, 2021}},
pages = {43--52},
publisher = {ACM},
year = {2021},
url = {https://doi.org/10.1145/3471158.3472248},
doi = {https://doi.org/10.1145/3471158.3472248}
}