Can Entanglement-Induced Feature-Map Designs Improve Projected Quantum Kernels?
This work exposes the structural capabilities of PQKs by isolating and evaluating their native inductive bias through comparisons between untuned and tuned PQKs and proposes novel quantum feature maps that leverage two-qubit entanglement to capture multivariate correlations in IoT data.
Ravi Kumar Jha, Hsuan-Yin Lin, E. Rosnes
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