Towards the Flatter Landscape and Better Generalization in Federated Learning under Client-level Differential Privacy
To defend the inference attacks and mitigate the sensitive information leakages in Federated Learning (FL), client-level Differentially Private FL (DPFL) is the de-facto standard for privacy protection by clipping local updates and adding random noise. However, existing DPFL methods tend to make a s...
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Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - PP(2025) vom: 11. Aug.
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| 1. Verfasser: |
Shi, Yifan
(VerfasserIn) |
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| Weitere Verfasser: |
Wei, Kang,
Shen, Li,
Liu, Yingqi,
Wang, Xueqian,
Yuan, Bo,
Tao, Dacheng |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2025
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article |
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