  Blind quantum machine learning (BQML) enables a classical client with little
quantum technology to delegate a remote quantum machine learning to the quantum
server in such a approach that the privacy data is preserved. Here we propose
the first BQML protocol that the client can classify two-dimensional vectors to
different clusters, resorting to a remote small-scale photon quantum
computation processor. During the protocol, the client is only required to
rotate and measure the single qubit. The protocol is secure without leaking any
relevant information to the Eve. Any eavesdropper who attempts to intercept and
disturb the learning process can be noticed. In principle, this protocol can be
used to classify high dimensional vectors and may provide a new viewpoint and
application for quantum machine learning.
