A Near-Optimal Algorithm for L1-Difference

Computer Science – Data Structures and Algorithms

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

We give the first L_1-sketching algorithm for integer vectors which produces nearly optimal sized sketches in nearly linear time. This answers the first open problem in the list of open problems from the 2006 IITK Workshop on Algorithms for Data Streams. Specifically, suppose Alice receives a vector x in {-M,...,M}^n and Bob receives y in {-M,...,M}^n, and the two parties share randomness. Each party must output a short sketch of their vector such that a third party can later quickly recover a (1 +/- eps)-approximation to ||x-y||_1 with 2/3 probability given only the sketches. We give a sketching algorithm which produces O(eps^{-2}log(1/eps)log(nM))-bit sketches in O(n*log^2(nM)) time, independent of eps. The previous best known sketching algorithm for L_1 is due to [Feigenbaum et al., SICOMP 2002], which achieved the optimal sketch length of O(eps^{-2}log(nM)) bits but had a running time of O(n*log(nM)/eps^2). Notice that our running time is near-linear for every eps, whereas for sufficiently small values of eps, the running time of the previous algorithm can be as large as quadratic. Like their algorithm, our sketching procedure also yields a small-space, one-pass streaming algorithm which works even if the entries of x,y are given in arbitrary order.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

A Near-Optimal Algorithm for L1-Difference does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A Near-Optimal Algorithm for L1-Difference, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Near-Optimal Algorithm for L1-Difference will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-98026

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.