Bilevel optimization learns client weights to defend fairness in one-shot collaborative ML by anchoring to a small trusted root dataset at the server.
Data poisoning attacks against federated learning systems
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Robust Server Defense Against Unreliable Clients in One-Shot Fair Collaborative Machine Learning
Bilevel optimization learns client weights to defend fairness in one-shot collaborative ML by anchoring to a small trusted root dataset at the server.