On The Estimation Of Latent Distances Using Graph Distances

ELECTRONIC JOURNAL OF STATISTICS(2021)

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摘要
We are given the adjacency matrix of a geometric graph and the task of recovering the latent positions. We study one of the most popular approaches which consists in using the graph distances and derive error bounds under various assumptions on the link function. In the simplest case where the link function is proportional to an indicator function, the bound matches an information lower bound that we derive.
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关键词
Latent positions, multidimensional scaling, graph embedding, graph distances, random geometric graphs
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