Approximation algorithms for projective clustering

  • Authors:
  • Pankaj K. Agarwal;Cecilia M. Procopiuc

  • Affiliations:
  • Center for Geometric and Biological Computing, Department of Computer Science, Box 90129, Duke University, Durham, NC;AT&T Labs, 180 Park Ave., Box 971, Florham Park, NJ

  • Venue:
  • Journal of Algorithms
  • Year:
  • 2003

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Abstract

We consider the following two instances of the projective clustering problem: Given a set S of n points in Rd and an integer k 0, cover S by k slabs (respectively d-cylinders) so that the maximum width of a slab (respectively the maximum diameter of a d-cylinder) is minimized. Let w* be the smallest value so that S can be covered by k slabs (respectively d-cylinders), each of width (respectively diameter) at most w*. This paper contains three main results: (i) For d = 2, we present a randomized algorithm that computes O(k log k) strips of width at most w* that cover S. Its expected running time is O(nk2log4n) if k2 log k ≤ n; for larger values of k, the expected running time is O(n2/3k8/3log14/3n). (ii) For d = 3, a cover of S by O(k log k) slabs of width at most w* can be computed in expected time O(n3/2k9/4polygon(n)).(iii) We compute a cover of S ⊂ Rd by O(dk log k) d-cylinders of diameter at most 8w* in expected time O(dnk3 log4 n). We also present a few extensions of this result.