English(EN) Consistency of Lloyd's Algorithm Under Perturbations

Lloyd算法在扰动样本下的聚类一致性已获证明

作者 PulseAugur 编辑部 · [1 个来源] · 2026-04-28 04:00

研究人员分析了Lloyd算法（一种流行的无监督聚类方法）在应用于扰动数据时的收敛性。他们证明，即使存在小的扰动，只要初始化得当，该算法在对数次迭代后仍能保持误聚类率的指数界限。这一理论保证也适用于衡量派生聚类统计显著性的流水线，对网络分析和时间序列分析等领域的谱聚类应用具有启示意义。 AI

影响为各种数据分析流水线中使用的聚类算法提供了理论保证，可能提高网络分析和时间序列等应用的可靠性。

排序理由这是一篇发表在arXiv上的研究论文，详细介绍了聚类算法的理论保证。

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arXiv cs.LG TIER_1 English(EN) · Dhruv Patel, Hui Shen, Shankar Bhamidi, Yufeng Liu, Vladas Pipiras · 2026-04-28 04:00

扰动下Lloyd算法的一致性

arXiv:2309.00578v2 Announce Type: replace Abstract: In the context of unsupervised learning, Lloyd's algorithm is one of the most widely used clustering algorithms. It has inspired a plethora of work investigating the correctness of the algorithm under various settings with groun…