On the O(1/t) Convergence Rate of Alternating Direction Method with Logarithmic-Quadratic Proximal Regularization

Min Tao, Xiaoming Yuan*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

38 Citations (Scopus)
25 Downloads (Pure)

Abstract

It was shown recently that the Douglas-Rachford alternating direction method of multipliers can be combined with the logarithmic-quadratic proximal regularization for solving a class of variational inequalities with separable structures. This paper further shows a worst-case O(1/t) convergence rate for this algorithm where a general Glowinski relaxation factor is used.

Original languageEnglish
Pages (from-to)1431-1448
Number of pages18
JournalSIAM Journal on Optimization
Volume22
Issue number4
DOIs
Publication statusPublished - 31 Oct 2012

Scopus Subject Areas

  • Software
  • Theoretical Computer Science

User-Defined Keywords

  • Alternating direction method of multipliers
  • Convergence rate
  • Glowinski's relaxation factor
  • Logarithmic-quadratic proximal regularization
  • Variational inequality

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