Approximation algorithms for low-distortion embeddings into low-dimensional spaces

  • Authors:
  • Mihai Bǎ/doiu;Kedar Dhamdhere;Anupam Gupta;Yuri Rabinovich;Harald Rä/cke;R. Ravi;Anastasios Sidiropoulos

  • Affiliations:
  • MIT Computer Science and Artificial Intelligence Laboratory/ Cambridge, MA;Carnegie Mellon University/ Pittsburgh, PA;Carnegie Mellon University/ Pittsburgh, PA;University of Haifa/ Haifa, Iarael;Carnegie Mellon University/ Pittsburgh, PA;Carnegie Mellon University/ Pittsburgh, PA;MIT Computer Science and Artificial Intelligence Laboratory/ Cambridge, MA

  • Venue:
  • SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
  • Year:
  • 2005

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Abstract

We present several approximation algorithms for the problem of embedding metric spaces into a line, and into the two-dimensional plane. Among other results, we give an O(√n)-approximation algorithm for the problem of finding a line embedding of a metric induced by a given unweighted graph, that minimizes the (standard) multiplicative distortion. We give an improved Õ(n1/3) approximation for the case of metrics generated by unweighted trees. This is the first result of this type.