Balancing Privacy and Utility in Split Learning: An Adversarial Channel Pruning-Based Approach
Machine Learning (ML) has been exploited across diverse fields with significant success. However, the deployment of ML models on resource-constrained devices, such as edge devices, has remained challenging due to the limited computing resources. Moreover, training such models using private data is p...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10838505/ |
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