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A Novel Evolutionary Approach for Neural Architecture Search by Alessandro Bria; Paolo De Ciccio; Tiziana D’Alessandro; Francesco Fontanella is a book available to read on EtoBox.

What is A Novel Evolutionary Approach for Neural Architecture Search about?

Convolutional Neural Networks (CNNs) have proven to be an effective tool in many real-world applications. The main problem of CNNs is the lack of a well-defined and largely shared set of criteria for the choice of architecture for a given problem. This lack represents a drawback for this approach since the choice of architecture plays a crucial role in CNNs'performance. Usually, these architectures are manually designed by experts. However, such a design process is computationally intensive because of the trial-and-error process and also not easy to realize due to the high level of expertise required. Recently, to try to overcome those drawbacks, many techniques that automize the task of designing the architecture neural networks have been proposed. To denote these techniques has been defined the term "Neural Architecture Search" (NAS). Among the many methods available for NAS, Evolutionary Computation (EC) methods have recently gained much attention and success. In this paper, we present a novel approach based on evolutionary computation to optimize CNNs. The proposed approach is based on a newly devised structure which encodes both hyperparameters and the architecture of a CNN. T

Author

Alessandro Bria; Paolo De Ciccio; Tiziana D’Alessandro; Francesco Fontanella

Publisher

Springer International Publishing

Published

2023

Language

EN

ISBN

9783031311833

Subjects

Mathematics, Engineering, Computer Science