Parallel and Distributed Machine Learning Algorithms for Scalable Big Data Analytics

Henri Bal; Arindam Pal

doi:10.1016/j.future.2019.07.009

Parallel and Distributed Machine Learning Algorithms for Scalable Big Data Analytics

Henri Bal, Arindam Pal^*

^*Corresponding author for this work

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Abstract

This editorial is for the Special Issue of the journal Future Generation Computing Systems, consisting of the selected papers of the 6th International Workshop on Parallel and Distributed Computing for Large Scale Machine Learning and Big Data Analytics (ParLearning 2017). In this editorial, we have given a high-level overview of the 4 papers contained in this special issue, along with references to some of the related works.

Original language	English
Pages (from-to)	1159-1161
Number of pages	3
Journal	Future Generation Computer Systems
Volume	108
Early online date	10 Jul 2019
DOIs	https://doi.org/10.1016/j.future.2019.07.009
Publication status	Published - Jul 2020

Funding

We would like to thank the general chair of ParLearning 2017, Anand Panangadan (California State University, Fullerton, USA), and all the reviewers of this special issue.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Parallel and Distributed Machine Learning Algorithms for Scalable Big Data AnalyticsFinal published version, 364 KBLicence: Article 25fa Dutch Copyright Act

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Parallel and Distributed Machine Learning Algorithms for Scalable Big Data Analytics

Abstract

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UN SDGs

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