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Privacy-aware Berrut Approximated Coded Computing for Federated Learning
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DOI：10.1016/j.jnca.2025.104280.png)
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Abstract
En 中文
• We propose a CDC solution able to guarantee privacy and compute arbitrary functions. • We have extended our proposal to FL scenarios with multiple data owners. • We have adapted our scheme to support optimized secure matrix multiplications.
Keywords:
Coded distributed computing
Privacy
Federated Learning
Secure Multi-Party Computation
Decentralized computation
Non-linearity
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