Continuous Cartesian Genetic Programming based representation for multi-objective neural architecture search

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@Article{GARCIAGARCIA:2023:asoc,

• author = "Cosijopii Garcia-Garcia and Alicia Morales-Reyes and Hugo Jair Escalante",
• title = "Continuous Cartesian Genetic Programming based representation for multi-objective neural architecture search",
• journal = "Applied Soft Computing",
• volume = "147",
• pages = "110788",
• year = "2023",
• ISSN = "1568-4946",
• DOI = "doi:10.1016/j.asoc.2023.110788",
• URL = "https://www.sciencedirect.com/science/article/pii/S1568494623008062",
• keywords = "genetic algorithms, genetic programming, Neural architecture search, ANN, Cartesian genetic programming, Convolutional neural network, Multi-objective optimization",
• abstract = "We propose a novel neural architecture search (NAS) approach for the challenge of designing convolutional neural networks (CNNs) that achieve a good tradeoff between complexity and accuracy. We rely on Cartesian genetic programming (CGP) and integrated real-based and block-chained CNN representation, for optimization using multi-objective evolutionary algorithms (MOEAs) in the continuous domain. We introduce two variants, CGP-NASV1 and CGP-NASV2, which differ in the granularity of their respective search spaces. To evaluate the proposed algorithms, we used the non-dominated sorting genetic algorithm II (NSGA-II) on the CIFAR-10, CIFAR-100,and SVHN datasets. Additionally, we extended the empirical analysis while maintaining the same solution representation to assess other searching techniques such as differential evolution (DE), the multi-objective evolutionary algorithm based on decomposition (MOEA/D), and the S metric selection evolutionary multi-objective algorithm (SMS-EMOA). The experimental results demonstrate that our approach exhibits competitive classification performance and model complexity compared to state-of-the-art methods",

}

Genetic Programming entries for Cosijopii Garcia-Garcia Alicia Morales-Reyes Hugo Jair Escalante

Citations