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English(EN) Optimal Clustering of Multi-layer Networks under Mixture Block Models

新方法优化混合块模型下的多层网络聚类

研究人员开发了一种新颖的两阶段估计器,用于在混合块模型下对多层网络进行聚类。该方法结合了基于张量的初始化、节点和样本分割以及基于似然的精炼,即使在极端稀疏的情况下也能实现最佳的网络聚类误差率。该框架已通过混合多层泊松块模型扩展到处理计数加权网络,并通过数值研究和真实数据分析进行了演示。 AI

排序理由 该聚类包含一篇关于网络分析新统计方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.4]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新方法优化混合块模型下的多层网络聚类

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该聚类包含一篇关于网络分析新统计方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.4]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Zhongyuan Lyu, Ting Li, Dong Xia ·

    混合块模型下多层网络的最佳聚类

    arXiv:2311.15598v2 Announce Type: replace-cross Abstract: We study clustering for multi-layer networks, where each observation is an undirected network measured on the same set of vertices. Under the mixture multi-layer stochastic block model (MMSBM), each network is generated fr…