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 Tools annual

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 monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

We propose a method for zeroth order stochastic convex optimization thatattains the suboptimality rate of $\tilde{\mathcal{O}}(n^{7}T^{-1/2})$ after$T$ queries for a convex bounded function $f:{\mathbb R}^n\to{\mathbb R}$. Themethod is based on a random walk (the \emph{Ball Walk}) on the epigraph of thefunction. The randomized approach circumvents the problem of gradientestimation, and appears to be less sensitive to noisy function evaluationscompared to noiseless zeroth order methods.

On Zeroth-Order Stochastic Convex Optimization via Random Walks