• Media type: E-Article; Electronic Conference Proceeding; Text
  • Title: The Johnson-Lindenstrauss Lemma Is Optimal for Linear Dimensionality Reduction
  • Contributor: Larsen, Kasper Green [Author]; Nelson, Jelani [Author]
  • imprint: Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2016
  • Language: English
  • DOI: https://doi.org/10.4230/LIPIcs.ICALP.2016.82
  • Keywords: lower bounds ; dimensionality reduction ; Johnson-Lindenstrauss
  • Origination:
  • Footnote: Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
  • Description: For any n > 1, 0 < epsilon < 1/2, and N > n^C for some constant C > 0, we show the existence of an N-point subset X of l_2^n such that any linear map from X to l_2^m with distortion at most 1 + epsilon must have m = Omega(min{n, epsilon^{-2}*lg(N)). This improves a lower bound of Alon [Alon, Discre. Mathem., 1999], in the linear setting, by a lg(1/epsilon) factor. Our lower bound matches the upper bounds provided by the identity matrix and the Johnson-Lindenstrauss lemma [Johnson and Lindenstrauss, Contem. Mathem., 1984].
  • Access State: Open Access