Improving the accuracy and stability of privacy-aware Shapley data valuation
Abstract The integration of privacy-preserving mechanisms like differential privacy into data valuation based on Shapley values introduces systematic noise, significantly degrading the accuracy and stability of estimates—a challenge not adequately addressed by existing methods. To address this, we p...
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| Principais autores: | , , |
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| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
Springer
2026-05-01
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| Serier: | Discover Applied Sciences |
| Fag: | |
| Online adgang: | https://doi.org/10.1007/s42452-026-08711-0 |
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