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/

Zendy Plus

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

Zendy Tools

Zendy Open

The classical perceptron rule provides a varying upper bound on the maximummargin, namely the length of the current weight vector divided by the totalnumber of updates up to that time. Requiring that the perceptron updates itsinternal state whenever the normalized margin of a pattern is found not toexceed a certain fraction of this dynamic upper bound we construct a newapproximate maximum margin classifier called the perceptron with dynamic margin(PDM). We demonstrate that PDM converges in a finite number of steps and derivean upper bound on them. We also compare experimentally PDM with otherperceptron-like algorithms and support vector machines on hard margin tasksinvolving linear kernels which are equivalent to 2-norm soft margin.

The Perceptron with Dynamic Margin