A randomized feature map classifier constructed by sampling from random quantum circuits with parametrized rotations matches the performance of standard classical kernel methods.
Weighted sums of random kitchen sinks: Replacing minimization with randomization in learning
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Machine Learning Kernel Method from a Quantum Generative Model
A randomized feature map classifier constructed by sampling from random quantum circuits with parametrized rotations matches the performance of standard classical kernel methods.