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Evolutionary Deep Neural Architecture Search

Evolutionary Deep Neural Architecture Search

ScienceTechnology
Pages
331
Published
2022
Language
English

Synopsis

This book explores the cutting-edge field of Evolutionary Deep Neural Architecture Search (EDNAS). It details methods for automatically designing optimal deep neural network architectures using evolutionary algorithms. Readers will find comprehensive insights into the theoretical foundations and practical applications of EDNAS, aiming to advance the efficiency and performance of AI systems.

Prose complexity
10/10

Vibe

InformativeIntellectualComplexThought-Provoking

Genres

Science Technology

Authors

M
Mengjie Zhang

Mengjie Zhang is a researcher who focuses on machine learning and artificial intelligence. He is the author of Evolutionary Deep Neural Architecture Search, a technical book exploring computer science methods.

Y
Yanan Sun

Yanan Sun writes about machine learning and computer science. He is the author of Evolutionary Deep Neural Architecture Search, a technical book focused on automated system design.