Differentially Private Graph Neural Networks for Whole-Graph Classification
Graph Neural Networks (GNNs) have established themselves as state-of-the-art for many machine learning applications such as the analysis of social and medical networks. Several among these datasets contain privacy-sensitive data. Machine learning with differential privacy is a promising technique to...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 45(2023), 6 vom: 12. Juni, Seite 7308-7318
|
|---|
| 1. Verfasser: |
Mueller, Tamara T
(VerfasserIn) |
|---|
| Weitere Verfasser: |
Paetzold, Johannes C,
Prabhakar, Chinmay,
Usynin, Dmitrii,
Rueckert, Daniel,
Kaissis, Georgios |
|---|
| Format: | Online-Aufsatz
|
|---|
| Sprache: | English |
|---|
| Veröffentlicht: |
2023
|
|---|
| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
|
|---|
| Schlagworte: | Journal Article |
|---|