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

In this work we consider the problem of repeated hyperparameter and neuralarchitecture search (HNAS). We propose an extension of Successive Halving thatis able to leverage information gained in previous HNAS problems with the goalof saving computational resources. We empirically demonstrate that our solutionis able to drastically decrease costs while maintaining accuracy and beingrobust to negative transfer. Our method is significantly simpler than competingtransfer learning approaches, setting a new baseline for transfer learning inHNAS.

A resource-efficient method for repeated HPO and NAS problems