A Hybrid Approach to Privacy-Preserving Federated Learning (Extended Abstract)
| dc.contributor.author | Truex, Stacey | |
| dc.contributor.author | Baracaldo, Nathalie | |
| dc.contributor.author | Anwar, Ali | |
| dc.contributor.author | Streinke, Thomas | |
| dc.contributor.author | Ludwig, Heiko | |
| dc.contributor.author | Zhang, Rui | |
| dc.contributor.author | Zhou, Yi | |
| dc.date.accessioned | 2019-11-20T12:38:36Z | |
| dc.date.available | 2019-11-20T12:38:36Z | |
| dc.date.issued | 2019 | |
| dc.identifier.doi | 10.1007/s00287-019-01205-x | |
| dc.identifier.pissn | 0170-6012 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/30201 | |
| dc.language.iso | en | |
| dc.publisher | Springer Verlag | |
| dc.relation.ispartof | Informatik Spektrum: Vol. 42, No. 5 | |
| dc.title | A Hybrid Approach to Privacy-Preserving Federated Learning (Extended Abstract) | en |
| dc.type | Text/Journal Article | |
| gi.citation.endPage | 357 | |
| gi.citation.publisherPlace | Berlin Heidelberg | |
| gi.citation.startPage | 356 | |
| gi.conference.sessiontitle | Hauptbeitrag |