EvoDeep: A new evolutionary approach for automatic Deep Neural Networks parametrisation

Title
EvoDeep: A new evolutionary approach for automatic Deep Neural Networks parametrisation
Authors
Keywords
Deep Learning, Evolutionary Algorithms, Finite-State Machines, Automated parametrisation
Journal
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
Volume 117, Issue -, Pages 180-191
Publisher
Elsevier BV
Online
2018-05-02
DOI
10.1016/j.jpdc.2017.09.006

Ask authors/readers for more resources

Reprint

Contact the author

Create your own webinar

Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.

Create Now

Become a Peeref-certified reviewer

The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.

Get Started