A Quasi-isometric Embedding Algorithm
classification
📊 stat.ML
cs.CGcs.LG
keywords
embeddingmanifoldalgorithmdatadimensionprojectionbounddistorts
read the original abstract
The Whitney embedding theorem gives an upper bound on the smallest embedding dimension of a manifold. If a data set lies on a manifold, a random projection into this reduced dimension will retain the manifold structure. Here we present an algorithm to find a projection that distorts the data as little as possible.
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