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

ASYNC is a framework that supports the implementation of asynchrony andhistory for optimization methods on distributed computing platforms. Thepopularity of asynchronous optimization methods has increased in distributedmachine learning. However, their applicability and practical experimentation ondistributed systems are limited because current bulk-processing cloud enginesdo not provide a robust support for asynchrony and history. With introducingthree main modules and bookkeeping system-specific and application parameters,ASYNC provides practitioners with a framework to implement asynchronous machinelearning methods. To demonstrate ease-of-implementation in ASYNC, thesynchronous and asynchronous variants of two well-known optimization methods,stochastic gradient descent and SAGA, are demonstrated in ASYNC.

ASYNC: A Cloud Engine with Asynchrony and History for Distributed Machine Learning