A parallel and distributed stochastic gradient descent implementation using commodity clusters

A parallel and distributed stochastic gradient descent implementation using commodity clusters

Abstract Deep Learning is an increasingly important subdomain of artificial intelligence, which benefits from training on Big Data. The size and complexity of the model combined with the size of the training dataset makes the training process very computationally and temporally expensive. Accelerati...

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Bibliographic Details
Main Authors: Robert K. L. Kennedy, Taghi M. Khoshgoftaar, Flavio Villanustre, Timothy Humphrey
Format: Article
Language:English
Published: SpringerOpen 2019-02-01
Series:Journal of Big Data
Subjects:
Parallel stochastic gradient descent
Parallel and distributed processing
Deep learning
Big data
Neural network
Cluster computer
Online Access:http://link.springer.com/article/10.1186/s40537-019-0179-2

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http://link.springer.com/article/10.1186/s40537-019-0179-2

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