Meta data
- BibTeX key
- conf/www/0003FFSTXL22
- entry type
- inproceedings
- booktitle
- WWW
- year
- 2022
- pages
- 732-742
- publisher
- ACM
- crossref
- conf/www/2022
- ee
- https://doi.org/10.1145/3485447.3512233
- isbn
- 978-1-4503-9096-5
- url
- http://dblp.uni-trier.de/db/conf/www/www2022.html#0003FFSTXL22
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- please select -%0 Conference Paper
%1 conf/www/0003FFSTXL22
%A Yang, Xue
%A Feng, Yan
%A Fang, Weijun
%A Shao, Jun
%A Tang, Xiaohu
%A Xia, Shu-Tao
%A Lu, Rongxing
%B WWW
%D 2022
%E Laforest, Frédérique
%E Troncy, Raphaël
%E Simperl, Elena
%E Agarwal, Deepak
%E Gionis, Aristides
%E Herman, Ivan
%E Médini, Lionel
%I ACM
%K dblp
%P 732-742
%T An Accuracy-Lossless Perturbation Method for Defending Privacy Attacks in Federated Learning.
%U http://dblp.uni-trier.de/db/conf/www/www2022.html#0003FFSTXL22
%@ 978-1-4503-9096-5
@inproceedings{conf/www/0003FFSTXL22,
added-at = {2023-05-02T00:00:00.000+0200},
author = {Yang, Xue and Feng, Yan and Fang, Weijun and Shao, Jun and Tang, Xiaohu and Xia, Shu-Tao and Lu, Rongxing},
biburl = {https://www.bibsonomy.org/bibtex/2843538d0217280e3072a1d7c1e1718a6/dblp},
booktitle = {WWW},
crossref = {conf/www/2022},
editor = {Laforest, Frédérique and Troncy, Raphaël and Simperl, Elena and Agarwal, Deepak and Gionis, Aristides and Herman, Ivan and Médini, Lionel},
ee = {https://doi.org/10.1145/3485447.3512233},
interhash = {96bf15968181592cd9357ad8389d2909},
intrahash = {843538d0217280e3072a1d7c1e1718a6},
isbn = {978-1-4503-9096-5},
keywords = {dblp},
pages = {732-742},
publisher = {ACM},
timestamp = {2024-04-09T12:55:05.000+0200},
title = {An Accuracy-Lossless Perturbation Method for Defending Privacy Attacks in Federated Learning.},
url = {http://dblp.uni-trier.de/db/conf/www/www2022.html#0003FFSTXL22},
year = 2022
}