Spectral embedding of weighted graphs
| Autor: | Gallagher, Ian, Jones, Andrew, Bertiger, Anna, Priebe, Carey, Rubin-Delanchy, Patrick |
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| Rok vydání: | 2019 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | When analyzing weighted networks using spectral embedding, a judicious transformation of the edge weights may produce better results. To formalize this idea, we consider the asymptotic behavior of spectral embedding for different edge-weight representations, under a generic low rank model. We measure the quality of different embeddings -- which can be on entirely different scales -- by how easy it is to distinguish communities, in an information-theoretic sense. For common types of weighted graphs, such as count networks or p-value networks, we find that transformations such as tempering or thresholding can be highly beneficial, both in theory and in practice. Comment: 27 pages, 5 figures |
| Databáze: | arXiv |
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