Quantum spectral clustering algorithm for unsupervised learning

Clustering is one of the most crucial problems in unsupervised learning, and the well-known k -means algorithm can be implemented on a quantum computer with a significant speedup. However, for the clustering problems that cannot be solved using the k -means algorithm, a powerful method called spectr...

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Vydané v:	Science China. Information sciences Ročník 65; číslo 10; s. 200504
Hlavní autori:	Li, Qingyu, Huang, Yuhan, Jin, Shan, Hou, Xiaokai, Wang, Xiaoting
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Beijing Science China Press 01.10.2022 Springer Nature B.V
Predmet:	Algorithms Circuit design Clustering Computer Science Datasets Design Eigenvalues Eigenvectors Entangled states Information Systems and Communication Service Interdisciplinary subjects Machine learning Microprocessors Quantum computers Quantum computing Quantum entanglement Random access memory Research Paper Science Unsupervised learning Grover’s search quantum algorithm quantum phase estimation machine learning Hamiltonian simulation spectral clustering
ISSN:	1674-733X, 1869-1919
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