Year: 2015
Type: preprint
Abstract: 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.
Source: arXiv (Cornell University)
Authors: Sheng, Yu-Bo, Zhou, Lan
Institution: Nanjing University of Posts and Telecommunications
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: G1245523348, G4690246023
OpenAlex ID: W1019089459