Asymptotic behaviors of semidefinite programming with a covariance perturbation

Ming Jie Gao, Ka Fai Cedric Yiu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

In this paper, we study asymptotic behaviors of semidefinite programming with a covariance perturbation. We obtain some moderate deviations, Cramér-type moderate deviations and a law of the iterated logarithm of estimates of the respective optimal value and optimal solutions when the covariance matrix is estimated by its sample covariance. As an example, we also apply the main results to the Minimum Trace factor Analysis.

Original languageEnglish
Pages (from-to)1631-1649
Number of pages19
JournalOptimization Letters
Volume13
Issue number7
DOIs
Publication statusPublished - Oct 2019

Keywords

  • Asymptotic
  • Law of the iterated logarithm
  • Minimum trace factor analysis
  • Moderate deviations
  • Perturbation
  • Semidefinite programming

ASJC Scopus subject areas

  • Control and Optimization

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