A Novel Clustering Algorithm Based on Quantum Random Walk

dc.creatorLi, Qiang
dc.creatorHe, Yan
dc.creatorJiang, Jing-ping
dc.date2008-12-07
dc.date.accessioned2026-07-07T12:10:06Z
dc.date.available2026-07-07T12:10:06Z
dc.descriptionThe enormous successes have been made by quantum algorithms during the last decade. In this paper, we combine the quantum random walk (QRW) with the problem of data clustering, and develop two clustering algorithms based on the one dimensional QRW. Then, the probability distributions on the positions induced by QRW in these algorithms are investigated, which also indicates the possibility of obtaining better results. Consequently, the experimental results have demonstrated that data points in datasets are clustered reasonably and efficiently, and the clustering algorithms are of fast rates of convergence. Moreover, the comparison with other algorithms also provides an indication of the effectiveness of the proposed approach.
dc.description14 pages, 6 figures, 3 tables
dc.identifierhttps://arxiv.org/abs/0812.1357
dc.identifierhttp://arxiv.org/abs/0812.1357
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/209845
dc.subjectMachine Learning
dc.titleA Novel Clustering Algorithm Based on Quantum Random Walk
dc.typetext

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