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} }
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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