Transfer learning for linear regression with differential privacy
Abstract Transfer learning, as a machine learning approach to enhance model generalization, has found widespread applications across various domains. However, the risk of privacy leakage during the transfer process remains a crucial consideration. Differential privacy, with its rigorous mathematical...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2024-12-01
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| Series: | Complex & Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s40747-024-01759-8 |
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