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

The robustness of distributed optimization is an emerging field of study,motivated by various applications of distributed optimization includingdistributed machine learning, distributed sensing, and swarm robotics. With therapid expansion of the scale of distributed systems, resilient distributedalgorithms for optimization are needed, in order to mitigate system failures,communication issues, or even malicious attacks. This survey investigates thecurrent state of fault-tolerance research in distributed optimization, and aimsto provide an overview of the existing studies on both fault-tolerantdistributed optimization theories and applicable algorithms.

A Survey on Fault-tolerance in Distributed Optimization and Machine Learning