
Federated Learning with Quantum Neural Networks and Fully Homomorphic Encryption provides a novel computing paradigm shift for privacy-preserving machine learning, addressing challenges in communication efficiency, data privacy, and computational overhead.


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federated-quantum-neural-networks-with-fully-homomorphic-encryption-a-privacy-preserving-approach-to-distributed-machine-learning


Federated Quantum Neural Networks with Fully Homomorphic Encryption: A Privacy-Preserving Approach to Distributed Machine Learning
