Generalization in Quantum Machine Learning: a Quantum Information Perspective

no code implementations • 17 Feb 2021 • Leonardo Banchi, Jason Pereira, Stefano Pirandola

Here we establish a link between quantum machine learning classification and quantum hypothesis testing (state and channel discrimination) and then show that the accuracy and generalization capability of quantum classifiers depend on the (R\'enyi) mutual informations $I(C{:}Q)$ and $I_2(X{:}Q)$ between the quantum state space $Q$ and the classical parameter space $X$ or class space $C$.

BIG-bench Machine Learning Classification +1