Deterministic strongly polynomial algorithm for matrix scaling and approximate permanents

Nathan Linial, Alex Samorodnitsky, Avi Wigderson

Research output: Contribution to journalConference articlepeer-review

48 Scopus citations

Abstract

We present a deterministic strongly polynomial algorithm that computes the permanent of a nonnegative n×n matrix to within a multiplicative factor of en. To this end we develop the first strongly polynomial time algorithm for matrix scaling - an important nonlinear optimization problem with many applications. Our work suggests a (slow) decision algorithm for bipartite perfect matching, conceptually different from known approaches.

Original languageEnglish
Pages (from-to)644-652
Number of pages9
JournalConference Proceedings of the Annual ACM Symposium on Theory of Computing
StatePublished - 1998
Externally publishedYes
EventProceedings of the 1998 30th Annual ACM Symposium on Theory of Computing - Dallas, TX, USA
Duration: 23 May 199826 May 1998

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