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Improving the Johnson-Lindenstrauss Lemma

Published 10 May 2010 in stat.ML | (1005.1440v1)

Abstract: The Johnson-Lindenstrauss Lemma allows for the projection of nn points in p−p-dimensional Euclidean space onto a k−k-dimensional Euclidean space, with $k \ge \frac{24\ln \emph{n}}{3\epsilon^2-2\epsilon^3}$, so that the pairwise distances are preserved within a factor of 1±ϵ1\pm\epsilon. Here, working directly with the distributions of the random distances rather than resorting to the moment generating function technique, an improvement on the lower bound for kk is obtained. The additional reduction in dimension when compared to bounds found in the literature, is at least 13%13\%, and, in some cases, up to 30%30\% additional reduction is achieved. Using the moment generating function technique, we further provide a lower bound for kk using pairwise L2L_2 distances in the space of points to be projected and pairwise L1L_1 distances in the space of the projected points. Comparison with the results obtained in the literature shows that the bound presented here provides an additional 36−40%36-40\% reduction.

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