Before revision:  We consider a classical-quantum learning problem in which the samples are quantum states with classical labels and the predictors are quantum measurements . To study this problem , we introduce a quantum counterpart of PAC framework .
After revision:  We consider a classical-quantum learning problem in which the samples are quantum states with classical labels and the predictors are quantum measurements that when applied to the next unseen quantum state predict its classical label. By integrating learning theory with quantum information , we introduce a quantum counterpart of PAC framework .