%0 Journal Article %1 journals/iotj/ZhuLLYXL22 %A Zhu, Linghui %A Liu, Xinyi %A Li, Yiming %A Yang, Xue %A Xia, Shu-Tao %A Lu, Rongxing %D 2022 %J IEEE Internet Things J. %K dblp %N 13 %P 11500-11512 %T A Fine-Grained Differentially Private Federated Learning Against Leakage From Gradients. %U http://dblp.uni-trier.de/db/journals/iotj/iotj9.html#ZhuLLYXL22 %V 9

@article{journals/iotj/ZhuLLYXL22, added-at = {2023-06-26T00:00:00.000+0200}, author = {Zhu, Linghui and Liu, Xinyi and Li, Yiming and Yang, Xue and Xia, Shu-Tao and Lu, Rongxing}, biburl = {https://www.bibsonomy.org/bibtex/2e273eb5706753e59627b3ee910079215/dblp}, ee = {https://doi.org/10.1109/JIOT.2021.3131258}, interhash = {fc7713e51df3ed1a1d21417dde4da79e}, intrahash = {e273eb5706753e59627b3ee910079215}, journal = {IEEE Internet Things J.}, keywords = {dblp}, number = 13, pages = {11500-11512}, timestamp = {2024-04-08T14:25:06.000+0200}, title = {A Fine-Grained Differentially Private Federated Learning Against Leakage From Gradients.}, url = {http://dblp.uni-trier.de/db/journals/iotj/iotj9.html#ZhuLLYXL22}, volume = 9, year = 2022 }