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Quantum Federated Learning Based on Bures--Uhlmann Geometry for Heterogeneous Noisy Clients

Emori, Haruki et al.
arXiv (All) · Papers
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machine-learningquantum-physics
Quantum federated learning enables collaborative model training across quantum devices without sharing raw data, and it faces the data and hardware heterogeneity inherent to noisy quantum devices. Utilizing the quantum geometric tensor is a natural remedy, yet pure-state approaches and diagonal appr
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