A Practical Federated Learning Framework for Small Number of Stakeholders.
Christian Schneebeli|Saikishore Kalloori|Severin Klingler
| Anthology ID: | DBLP:conf/wsdm/SchneebeliKK21 |
|---|---|
| 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: | 910-913 |
| URL: | https://doi.org/10.1145/3437963.3441702 |
| DOI: | https://doi.org/10.1145/3437963.3441702 |
| DBLP: | conf/wsdm/SchneebeliKK21 |
| BibTeX: |
@inproceedings{schneebeli-2021-practical,
author = {Christian Schneebeli and
Saikishore Kalloori and
Severin Klingler},
editor = {Liane Lewin-Eytan and
David Carmel and
Elad Yom-Tov and
Eugene Agichtein and
Evgeniy Gabrilovich},
title = {{A Practical Federated Learning Framework for Small Number of Stakeholders}},
booktitle = {{WSDM '21, The Fourteenth ACM International Conference on Web Search and Data Mining, Virtual Event, Israel, March 8-12, 2021}},
pages = {910--913},
publisher = {ACM},
year = {2021},
url = {https://doi.org/10.1145/3437963.3441702},
doi = {https://doi.org/10.1145/3437963.3441702}
}