Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding.

Yuke Hu|Wei Liang|Ruofan Wu|Kai Xiao|Weiqiang Wang|Xiaochen Li|Jinfei Liu|Zhan Qin


Anthology ID:DBLP:conf/www/HuLWXWLLQ23
Volume:Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023
Year:2023
Venue:The Web Conference (WWW)
Publisher:ACM
Pages:2306-2317
URL:https://doi.org/10.1145/3543507.3583450
DOI:https://doi.org/10.1145/3543507.3583450
DBLP:conf/www/HuLWXWLLQ23
BibTeX:
@inproceedings{hu-2023-quantifying, author = {Yuke Hu and Wei Liang and Ruofan Wu and Kai Xiao and Weiqiang Wang and Xiaochen Li and Jinfei Liu and Zhan Qin}, editor = {Ying Ding and Jie Tang and Juan F. Sequeda and Lora Aroyo and Carlos Castillo and Geert-Jan Houben}, title = {{Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding}}, booktitle = {{Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023}}, pages = {2306--2317}, publisher = {ACM}, year = {2023}, url = {https://doi.org/10.1145/3543507.3583450}, doi = {https://doi.org/10.1145/3543507.3583450} }