A coordinatewise domain scaling algorithm for M-convex function minimization

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

We present a polynomial time domain scaling algorithm for the minimization of an M-convex function. M-convex functions are nonlinear discrete functions with (poly)matroid structures, which are being recognized to play a fundamental role in tractable cases of discrete optimization. The novel idea of the algorithm is to use an individual scaling factor for each coordinate.

Original languageEnglish
Pages (from-to)21-35
Number of pages15
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2337 LNCS
Publication statusPublished - 2002
Externally publishedYes

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Function Minimization
Convex Minimization
Convex function
Scaling
Scaling Factor
Discrete Optimization
Matroid
Time Domain
Polynomial time
Polynomials

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

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title = "A coordinatewise domain scaling algorithm for M-convex function minimization",
abstract = "We present a polynomial time domain scaling algorithm for the minimization of an M-convex function. M-convex functions are nonlinear discrete functions with (poly)matroid structures, which are being recognized to play a fundamental role in tractable cases of discrete optimization. The novel idea of the algorithm is to use an individual scaling factor for each coordinate.",
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