Spectral sparsification of graphs

Joshua Batson, Daniel A. Spielman, Nikhil Srivastava, Shang‐Hua Teng

Communications of the ACM · 2013 · 156 citations · 32 references

Concepts

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.

References

32