一种基于量子随机游走的聚类算法
A Novel Clustering Algorithm Based on Quantum Random Walk
摘要：
在过去的十年里，量子算法取得了巨大的成功。本文将量子随机游走与数据聚类问题相结合，提出了两种基于一维量子随机游走的数据聚类算法。然后，研究了这些算法中由QRW引起的位置的概率分布，这也表明了获得更好结果的可能性。实验结果表明，该算法能够合理有效地对数据点进行聚类，并且具有较快的收敛速度。此外，与其他算法的比较也提供了所提出的方法的有效性的指示。
英文摘要：
The 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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
