Quantum advantage in unsupervised machine learning is limited to cases where density-matrix features absent from classical distributions can be exploited, with explicit examples showing strong dependence on input data and target observables.
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Limitations of Quantum Advantage in Unsupervised Machine Learning
Quantum advantage in unsupervised machine learning is limited to cases where density-matrix features absent from classical distributions can be exploited, with explicit examples showing strong dependence on input data and target observables.