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can we trade the number of samples required to learn a function for time In general, the answer to this question will be no, because there are two different scaling behaviors being conflated: a. Sample complexity: The number of samples sufficient to accurately learn a dataset, from any randomly sampled training set.$^1$ b. Algorithmic complexity: Some ...


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Time irreducible & Inaccessibility (philosophical + analytically): Interesting question! Let me start antichronological with your lovely example. Neal has 20/20 and Peter 20/80. You are saying that Peter needs to get closer to see the mountains and it's infrastructure clearly. So you are changing the equal base condition both had at the beginning. That's ...


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A few things I would consider: If you have a superposition of the data, weights, etc. I suspect (but am not entirely confident) that you may find a fully quantum neural network reduces to something very similar to a Grover's search over the network weights. An example of a similar reduction exists in quantum genetic algorithms (see this paper and this one) ...


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Qiskit ML VQC is a lightweight sub-class of sklearn SVC that supplies the quantum kernel to the SVC. You can therefore leverage sklearns capabilities to say save/restore models see https://scikit-learn.org/stable/modules/model_persistence.html#python-specific-serialization


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