Before revision: Advances in quantum information processing compel us to explore learning from quantum data . We consider a classical-quantum learning problem in which the samples are quantum states with classical labels and the predictors are quantum measurements .
After revision: Advances in quantum information processing compel us to explore learning from quantum data , in particular quantum state classification which has applications, among others, in classifying the separability of quantum states. In this learning model, there are n quantum states with classical labels and the predictors are quantum measurements .