Quantum automated learning trains a quantum classifier by imaginary-time-like dissipation, converging to the global minimum of a data-encoded Hamiltonian with a logarithmic generalization bound.
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Quantum automated learning with provable and explainable trainability
Quantum automated learning trains a quantum classifier by imaginary-time-like dissipation, converging to the global minimum of a data-encoded Hamiltonian with a logarithmic generalization bound.