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

We developed a corporative stochastic approximation (CSA) type algorithm forsemi-infinite programming (SIP), where the cut generation problem is solvedinexactly. First, we provide general error bounds for inexact CSA. Then, wepropose two specific random constraint sampling schemes to approximately solvethe cut generation problem. When the objective and constraint functions aregenerally convex, we show that our randomized CSA algorithms achieve an$\mathcal{O}(1/\sqrt{N})$ rate of convergence in expectation (in terms ofoptimality gap as well as SIP constraint violation). When the objective andconstraint functions are all strongly convex, this rate can be improved to$\mathcal{O}(1/N)$.

Corporative Stochastic Approximation with Random Constraint Sampling for Semi-Infinite Programming