Federated Online Learning to Rank with Evolution Strategies: A Reproducibility Study.
Shuyi Wang|Shengyao Zhuang|Guido Zuccon
| Anthology ID: | DBLP:conf/ecir/WangZZ21 |
|---|---|
| Volume: | Advances in Information Retrieval - 43rd European Conference on IR Research, ECIR 2021, Virtual Event, March 28 - April 1, 2021, Proceedings, Part II |
| Year: | 2021 |
| Venue: | European Conference on Advances in Information Retrieval (ECIR) |
| Publisher: | Springer |
| Pages: | 134-149 |
| URL: | https://doi.org/10.1007/978-3-030-72240-1_10 |
| DOI: | https://doi.org/10.1007/978-3-030-72240-1_10 |
| DBLP: | conf/ecir/WangZZ21 |
| BibTeX: |
@inproceedings{wang-2021-federated,
author = {Shuyi Wang and
Shengyao Zhuang and
Guido Zuccon},
editor = {Djoerd Hiemstra and
Marie-Francine Moens and
Josiane Mothe and
Raffaele Perego and
Martin Potthast and
Fabrizio Sebastiani},
title = {{Federated Online Learning to Rank with Evolution Strategies: A Reproducibility Study}},
booktitle = {{Advances in Information Retrieval - 43rd European Conference on IR Research, ECIR 2021, Virtual Event, March 28 - April 1, 2021, Proceedings, Part II}},
series = {Lecture Notes in Computer Science},
volume = {12657},
pages = {134--149},
publisher = {Springer},
year = {2021},
url = {https://doi.org/10.1007/978-3-030-72240-1_10},
doi = {https://doi.org/10.1007/978-3-030-72240-1_10}
}