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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper is devoted to the analysis of worst case complexity bounds forlinesearch-type derivative-free algorithms for the minimization of generalnon-convex smooth functions. We prove that two linesearch-type algorithms enjoythe same complexity properties which have been proved for pattern and directsearch algorithms. In particular, we consider two derivative-free algorithmsbased on two different linesearch techniques and manage to prove that thenumber of iterations and of function evaluations required to drive the norm ofthe gradient of the objective function below a given threshold $\epsilon$ is${\cal O}(\epsilon^{-2})$ in the worst case.

Worst case complexity bounds for linesearch-type derivative-free algorithms