English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

We propose a unified analysis for a class of infeasible-start predictor-corrector algorithms for semidefinite programming problems, using the Monteiro-Zhang unified direction. The algorithms are direct generalizations of the Mizuno-Todd-Ye predictor-corrector algorithm for linear programming. We show that the algorithms belonging to this class are globally convergent, provided the problem has a solution, and have the best known complexity. We also give simple sufficient conditions for superlinear convergence. Our results generalize the results obtained by Potra and Sheng for the infeasible-interior-point algorithm proposed by Kojima, Shida and Shindoh and Potra and Sheng.

On a general class of interior-point algorithms for semidefinite programming with polynomial complexity and superlinear convergence