方法证据记录
Quantum SVM
Quantum Support Vector Machine (QSVM) is a quantum machine learning algorithm combining quantum feature spaces with classical SVM training. Proposed by Rebentrost et al. in 2014, QSVM leverages quantum processors to compute kernel functions, potentially offering speedup for classification problems while remaining practical on near-term quantum devices.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Quantum Support Vector Machine
分类方法记录 · ml-model / quantum-computing
- Rebentrost, P., Mohseni, M., Lloyd, S. (2014). Quantum support vector machine for big data classification. Physical Review Letters, 113, 130503. · DOI 10.1103/PhysRevLett.113.130503
- Havlíček, V., Córcoles, A. D., Temme, K., et al. (2019). Supervised learning with quantum-enhanced feature spaces. Nature, 567, 209–212. · DOI 10.1038/s41586-019-0980-2
- Liu, Y., Arunachalam, S., Temme, K. (2021). A rigorous and robust quantum speed-up in supervised machine learning. arXiv preprint arXiv:2010.07471. · URL
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