Machine learning friendly set version of Johnson–Lindenstrauss lemma

作者：Mieczysław A. Kłopotek

摘要

The widely discussed and applied Johnson–Lindenstrauss (JL) Lemma has an existential form saying that for each set of data points Q in n-dimensional space, there exists a transformation f into an \(n'\)-dimensional space (\(n'

论文关键词：Johnson–Lindenstrauss lemma, Random projection, Sample distortion, Dimensionality reduction, Linear JL transform, k-means algorithm, Clusterability retention

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论文官网地址：https://doi.org/10.1007/s10115-019-01412-8