  The application of machine learning to quantum information processing has
recently attracted keen interest, particularly for the optimization of control
parameters in quantum tasks without any pre-programmed knowledge. By adapting
the machine learning technique, we present a novel protocol in which an
arbitrarily initialized device at a learner's location is taught by a provider
located at a distant place. The protocol is designed such that any external
learner who attempts to participate in or disrupt the learning process can be
prohibited or noticed. We numerically demonstrate that our protocol works
faithfully for single-qubit operation devices. A trade-off between the
inaccuracy and the learning time is also analyzed.
