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Invariance principle of random projection for the norm. (arXiv:2112.00300v2 [math.PR] UPDATED)
May 23, 2022, 1:11 a.m. | Juntao Duan, Ionel Popescu, Heinrich Matzinger
stat.ML updates on arXiv.org arxiv.org
Johnson-Lindenstrauss guarantees certain topological structure is preserved
under random projections when project high dimensional deterministic vectors to
low dimensional vectors. In this work, we try to understand how random matrix
affect norms of random vectors. In particular we prove the distribution of the
norm of random vector $X \in \mathbb{R}^n$, whose entries are i.i.d. random
variables, is preserved by random projection $S:\mathbb{R}^n \to \mathbb{R}^m$.
More precisely, \[ \frac{X^TS^TSX - mn}{\sqrt{\sigma^2 m^2n+2mn^2}}
\xrightarrow[\quad m/n\to 0 \quad ]{ m,n\to \infty } \mathcal{N}(0,1) …
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