Variance is a fundamental statistical measure in data analytics, representing the spread of a dataset. It's crucial for understanding data dispersion, but when it comes to unevenly distributed ...

Abstract: This article proposes a distributed adaptive training method for neural networks in switching communication graphs to deal with the problems concerned with massive data or privacy-related ...

In the era of big data, distributed graph processing frameworks have become important in processing large-scale graph datasets. Such distributed frameworks exhibit major advantages with respect to ...

Another distributed graph database worth comparing to GE is JanusGraph, a new project under the sponsorship of the Linux Foundation with contributions by Google, Hortonworks, and IBM.

Distributed algorithms for graph problems represent a vibrant area of study that addresses the challenges of decentralised computation across interconnected networks.