FedQP: Large-Scale Private and Flexible Federated Query Processing
State-of-the-art federated learning coordinates stochastic gradient descent across clients to refine shared model parameters while protecting individual datasets. Current methods require a uniform data model and are vulnerable to privacy attacks such as model inversion. The key challenge is in desig...
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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/10988771/ |
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