AdeptHEQ-FL integrates hybrid CNN-PQC models, adaptive homomorphic encryption, accuracy-weighted aggregation, and dynamic layer freezing in federated learning to gain accuracy on image datasets while lowering communication overhead.
Qamplifynet: pushing the boundaries of supply chain backo- rder prediction using interpretable hybrid quantum-classical neural network
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AdeptHEQ-FL: Adaptive Homomorphic Encryption for Federated Learning of Hybrid Classical-Quantum Models with Dynamic Layer Sparing
AdeptHEQ-FL integrates hybrid CNN-PQC models, adaptive homomorphic encryption, accuracy-weighted aggregation, and dynamic layer freezing in federated learning to gain accuracy on image datasets while lowering communication overhead.