Partial adversarial coverage in simulated quantum federated learning improves small-perturbation robustness with little clean-accuracy loss, but label-sorted non-IID data removes about half the robustness benefit.
Studying the impact of quantum-specific hyperparameters on hybrid quantum-classical neural networks,
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RobQFL: Robust Quantum Federated Learning in Adversarial Environment
Partial adversarial coverage in simulated quantum federated learning improves small-perturbation robustness with little clean-accuracy loss, but label-sorted non-IID data removes about half the robustness benefit.