%0 Thesis %1 bernau2022improved %A Bernau, Daniel %C Stuttgart %D 2022 %K diss oa phf05 ubs_10005 ubs_20007 ubs_30180 unibibliografie %R 10.18419/opus-12490 %T Improved usability of differential privacy in machine learning : techniques for quantifying the privacy-accuracy trade-off

@phdthesis{bernau2022improved, added-at = {2022-11-15T10:58:25.000+0100}, address = {Stuttgart}, author = {Bernau, Daniel}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/286d59730f8277fe53dd23282ed7f285e/unibiblio-3}, doi = {10.18419/opus-12490}, eventdate = {2022-10-07}, interhash = {978f8397d2b5ae1709685c2a4f52b1b1}, intrahash = {86d59730f8277fe53dd23282ed7f285e}, keywords = {diss oa phf05 ubs_10005 ubs_20007 ubs_30180 unibibliografie}, language = {eng}, school = {Universität Stuttgart}, supervisor = {Küsters, Ralf}, supervisorgnd = {1028953577}, timestamp = {2022-11-15T09:58:25.000+0100}, title = {Improved usability of differential privacy in machine learning : techniques for quantifying the privacy-accuracy trade-off}, type = {Dissertation}, year = 2022 }