Deep neural networks compression learning based on multiobjective evolutionary algorithms

This work addresses the problem of deep neural network compression, which is a promising technique to reduce the number of network parameters and/or speed up the network evaluation process significantly. Most of the existing methods rely on domain experts’ experience for the selection of hyperparame...

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Bibliographic Details

Published in:	Neurocomputing (Amsterdam) Vol. 378; pp. 260 - 269
Main Authors:	Huang, Junhao, Sun, Weize, Huang, Lei
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 22.02.2020
Subjects:	Evolutionary optimization Expensive optimization Neural network compression Pareto-optimal solutions Expensive optimization Pareto-optimal solutions Evolutionary optimization Neural network compression
ISSN:	0925-2312, 1872-8286
Online Access:	Get full text
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