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 show that the Subgradient algorithm is universal for online learning onthe simplex in the sense that it simultaneously achieves $O(\sqrt N)$ regretfor adversarial costs and $O(1)$ pseudo-regret for i.i.d costs. To the best ofour knowledge this is the first demonstration of a universal algorithm on thesimplex that is not a variant of Hedge. Since Subgradient is a popular andwidely used algorithm our results have immediate broad application.

Optimality of the Subgradient Algorithm in the Stochastic Setting