A linearly convergent dual-based gradient projection algorithm for quadratically constrained convex minimization

Amir Beck*, Marc Teboulle

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents a new dual formulation for quadratically constrained convex programs. The special structure of the derived dual problem allows us to apply the gradient projection algorithm to produce a simple explicit method involving only elementary vector-matrix operations, proven to converge at a linear rate.

Original languageEnglish
Pages (from-to)398-417
Number of pages20
JournalMathematics of Operations Research
Volume31
Issue number2
DOIs
StatePublished - 2006

Keywords

  • Convex minimization
  • Gradient projection algorithm
  • Quadratically constrained problems
  • Rate of convergence

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