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} }