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A Notion of Harmonic Clustering in Simplicial Complexes

机译:简单复群中的调和聚类的概念

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We outline a novel clustering scheme for simplicial complexes that produces clusters of simplices in a way that is sensitive to the homology of the complex. The method is inspired by, and can be seen as a higher-dimensional version of, graph spectral clustering. The algorithm involves only sparse eigenproblems, and is therefore computationally efficient. We believe that it has broad application as a way to extract features from simplicial complexes that often arise in topological data analysis.
机译:我们概述了一种简单的复杂络合物的聚类方案,该方案以对络合物的同源性敏感的方式生成单纯形团簇。该方法的灵感来自于图谱聚类,并且可以看作是图谱聚类的更高维度版本。该算法仅涉及稀疏本征问题,因此计算效率高。我们认为,它作为从拓扑数据分析中经常出现的简单复杂特征中提取特征的一种方法,具有广泛的应用。

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