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Near Optimal Dimensionality Reductions That Preserve Volumes

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Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques (APPROX 2008, RANDOM 2008)

Abstract

Let P be a set of n points in Euclidean space and let 0 < ε< 1. A well-known result of Johnson and Lindenstrauss states that there is a projection of P onto a subspace of dimension \(\mathcal{O}(\epsilon^{-2} \log n)\) such that distances change by at most a factor of 1 + ε. We consider an extension of this result. Our goal is to find an analogous dimension reduction where not only pairs but all subsets of at most k points maintain their volume approximately. More precisely, we require that sets of size s ≤ k preserve their volumes within a factor of (1 + ε)s − 1. We show that this can be achieved using \(\mathcal{O}(\max\{\frac{k}{\epsilon},\epsilon^{-2}\log n\})\) dimensions. This in particular means that for \(k = \mathcal{O}(\log n/\epsilon)\) we require no more dimensions (asymptotically) than the special case k = 2, handled by Johnson and Lindenstrauss. Our work improves on a result of Magen (that required as many as \(\mathcal{O}(k\epsilon^{-2}\log n)\) dimensions) and is tight up to a factor of \(\mathcal{O}(1/\epsilon)\). Another outcome of our work is an alternative and greatly simplified proof of the result of Magen showing that all distances between points and affine subspaces spanned by a small number of points are approximately preserved when projecting onto \(\mathcal{O}(k\epsilon^{-2}\log n)\) dimensions.

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Ashish Goel Klaus Jansen José D. P. Rolim Ronitt Rubinfeld

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© 2008 Springer-Verlag Berlin Heidelberg

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Magen, A., Zouzias, A. (2008). Near Optimal Dimensionality Reductions That Preserve Volumes. In: Goel, A., Jansen, K., Rolim, J.D.P., Rubinfeld, R. (eds) Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques. APPROX RANDOM 2008 2008. Lecture Notes in Computer Science, vol 5171. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85363-3_41

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  • DOI: https://doi.org/10.1007/978-3-540-85363-3_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85362-6

  • Online ISBN: 978-3-540-85363-3

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