Leveraging Gradient Noise for Detection and Filtering of Byzantine Clients
Distributed Learning enables multiple clients to collaboratively train large models on private, decentralized data. However, this setting faces a significant challenge: real-world datasets are inherently heterogeneous, and the distributed nature of the system makes it vulnerable to Byzantine attacks...
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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/11129040/ |
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