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Spectral sparsification of graphs: theory and algorithms

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Abstract

Graph sparsification is the approximation of an arbitrary graph by a sparse graph.

We explain what it means for one graph to be a spectral approximation of another and review the development of algorithms for spectral sparsification. In addition to being an interesting concept, spectral sparsification has been an important tool in the design of nearly linear-time algorithms for solving systems of linear equations in symmetric, diagonally dominant matrices. The fast solution of these linear systems has already led to breakthrough results in combinatorial optimization, including a faster algorithm for finding approximate maximum flows and minimum cuts in an undirected network.

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      cover image Communications of the ACM
      Communications of the ACM  Volume 56, Issue 8
      August 2013
      85 pages
      ISSN:0001-0782
      EISSN:1557-7317
      DOI:10.1145/2492007
      Issue’s Table of Contents

      Copyright © 2013 ACM

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      Publication History

      • Published: 1 August 2013

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