ESAE: Evolutionary Strategy-Based Architecture Evolution

Pages: 193 - 208
Published: Nov 22, 2019
Abstract
Although deep neural networks (DNNs) play important roles in many fields, the architecture design of DNNs can be challenging due to the difficulty of input data representation, the huge number of parameters and the complex layer relationships. To overcome the obstacles of architecture design, we developed a new method to generate the optimal structure of DNNs, named Evolutionary Strategy-based Architecture Evolution (ESAE), consisting of a...
Paper Details
Title
ESAE: Evolutionary Strategy-Based Architecture Evolution
Published Date
Nov 22, 2019
Pages
193 - 208
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