GLEE: Geometric Laplacian Eigenmap Embedding.

arXiv: Learning(2020)

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摘要
Graph embedding seeks to build a low-dimensional representation of a graph $G$. This low-dimensional representation is then used for various downstream tasks. One popular approach is Laplacian Eigenmaps (LE), which constructs a graph embedding based on the spectral properties of the Laplacian matrix of $G$. The intuition behind it, and many other embedding techniques, is that the embedding of a gr...
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关键词
graph embedding,graph Laplacian,simplex geometry
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