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...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Neurocomputing (Amsterdam) Jg. 378; S. 260 - 269
Hauptverfasser:	Huang, Junhao, Sun, Weize, Huang, Lei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 22.02.2020
Schlagworte:	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-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!