Quantum classifier with tailored quantum kernel

@article{Blank2019QuantumCW,
  title={Quantum classifier with tailored quantum kernel},
  author={C. Blank and D. Park and J. Rhee and Francesco Petruccione},
  journal={npj Quantum Information},
  year={2019},
  volume={6},
  pages={1-7}
}
  • C. Blank, D. Park, +1 author Francesco Petruccione
  • Published 2019
  • Computer Science, Physics
  • npj Quantum Information
  • Kernel methods have a wide spectrum of applications in machine learning. Recently, a link between quantum computing and kernel theory has been formally established, opening up opportunities for quantum techniques to enhance various existing machine-learning methods. We present a distance-based quantum classifier whose kernel is based on the quantum state fidelity between training and test data. The quantum kernel can be tailored systematically with a quantum circuit to raise the kernel to an… CONTINUE READING
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