Using maximally entangled training data exponentially flattens the loss landscape of highly expressive quantum models, limiting the loss improvement achievable in a fixed-size neighborhood.
Certain inequalities of kober and lazarevic type.The Journal of the Indian Mathematical Society, 89(1-2):01–07, 2022
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Loss Behavior in Supervised Learning with Entangled States
Using maximally entangled training data exponentially flattens the loss landscape of highly expressive quantum models, limiting the loss improvement achievable in a fixed-size neighborhood.