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Deterministic Length Reduction: Fast Convolution in Sparse Data and Applications

  • Amihood Amir
  • Oren Kapah
  • Ely Porat
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4580)

Abstract

In this paper a deterministic algorithm for the length reduction problem is presented. This algorithm enables a new tool for performing fast convolution in sparse data. The proposed algorithm performs the convolution in \(O(n_1 \log^3 n_1)\), where n 1 is the number of non-zero values in V 1. This algorithm assumes that V 1 is given in advance, and the V 2 is given in running time.

Keywords

Prime Number Vector Versus Sparse Data Deterministic Algorithm Deterministic Solution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Amihood Amir
    • 1
  • Oren Kapah
    • 1
  • Ely Porat
    • 1
  1. 1.Department of Computer Science, Bar-Ilan University, Ramat-Gan 52900Israel

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