English(EN) Improved approximation algorithms for capacitated cluster editing

新算法改进容量聚类编辑的近似效果

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-05 05:00

研究人员为容量聚类编辑问题开发了改进的近似算法，该问题旨在从有符号图中构建有界大小的不相交团，以最小化分歧。新算法建立在现有针对无容量版本的算法之上，实现了更好的近似比。具体来说，一种方法提供了具有 $2\alpha + 1$ 比率的缩小程序，而另一种使用 LP 采样和枢轴的混合方法显示出预期的成本为 $\frac 95 L + \frac 1{10} \OPT_k$ 或 $\frac {306}{203} L + \frac {50}{203} \OPT_k$。这些进展带来了具有 $(1.9 + \epsilon)$ 和 $(1.7537 + \epsilon)$ 比率的随机近似算法。 AI

排序理由学术论文，详细介绍了图论问题的新近似算法。[lever_c_demoted from research: ic=1 ai=0.1]

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arXiv cs.LG TIER_1 English(EN) · Cong Ma, Guangting Chen, Yong Chen, Guohui Lin, Jiaxuan Ma, Lusheng Wang · 2026-11-05 05:00

改进的容量聚类编辑近似算法

arXiv:2611.05916v1 Announce Type: cross Abstract: We study the minimum-disagreement cluster editing problem that, from a complete edge-signed graph, where a positive edge represents two vertices agreeing to each other while a negative represents a disagreement, constructs disjoin…

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改进的容量聚类编辑近似算法

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