MULTIOBJECTIVE COEVOLUTION OF DEEP NEURAL NETWORK ARCHITECTURES

An evolutionary AutoML framework called LEAF optimizes hyperparameters, network architectures and the size of the network. LEAF makes use of both evolutionary algorithms (EAs) and distributed computing frameworks. A multiobjective evolutionary algorithm is used to maximize the performance and minimi...

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Bibliographic Details
Main Authors LIANG, Jason Zhi, MIIKKULAINEN, Risto, MEYERSON, Elliott
Format Patent
LanguageEnglish
French
German
Published 26.01.2022
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Summary:An evolutionary AutoML framework called LEAF optimizes hyperparameters, network architectures and the size of the network. LEAF makes use of both evolutionary algorithms (EAs) and distributed computing frameworks. A multiobjective evolutionary algorithm is used to maximize the performance and minimize the complexity of the evolved networks simultaneously by calculating the Pareto front given a group of individuals that have been evaluated for multiple obj ectives.
Bibliography:Application Number: EP20190878418