Hardening quantum machine learning against adversaries
Hardening quantum machine learning against adversaries is a scholarly work, published in 2018 in ''New Journal of Physics''. The main subjects of the publication include quantum, quantum superposition, superposition principle, speedup, quantum information science, artificial intelligence, quantum computer, Hamiltonian, boosting, test oracle, quantum computing, quantum machine learning, theoretical computer science, quantum algorithm, machine learning, Benford's law, and computer science. The authors also introduce a new quantum approach for bagging and boosting that can use quantum superposition over the classifiers or splits of the training set to aggregate over many more models than would be possible classically.