Quantum Cross Entropy and Maximum Likelihood Principle. (arXiv:2102.11887v1 [quant-ph])

Quantum machine learning is an emerging field at the intersection of machine
learning and quantum computing. Classical cross entropy plays a central role in
machine learning. We define its quantum generalization, the quantum cross
entropy, and investigate its relations with the quantum fidelity and the
maximum likelihood principle. We also discuss its physical implications on
quantum measurements.

Source: https://arxiv.org/abs/2102.11887


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