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Author Teng, Shang-Hua ♦ Srivastava, Nikhil ♦ Batson, Joshua ♦ Spielman, Daniel A.
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
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.
Description Affiliation: Computer Science, USC (Teng, Shang-Hua) || Mathematics, MIT (Batson, Joshua) || Yale University (Spielman, Daniel A.) || Microsoft Research, Bangalore (Srivastava, Nikhil)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2005-08-01
Publisher Place New York
Journal Communications of the ACM (CACM)
Volume Number 56
Issue Number 8
Page Count 8
Starting Page 87
Ending Page 94

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Source: ACM Digital Library