The paper maps gate-model quantum neural networks into a constraint-machine framework and declares supervised learning and backpropagation optimal, but the proofs rely on textbook results and do not validate the proposed algorithms.
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Training Optimization for Gate-Model Quantum Neural Networks
The paper maps gate-model quantum neural networks into a constraint-machine framework and declares supervised learning and backpropagation optimal, but the proofs rely on textbook results and do not validate the proposed algorithms.