Iterative Structure-Based Genetic Programming for Neural Architecture Search

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{kapoor:2023:GECCOcomp,

• author = "Rahul Kapoor and Nelishia Pillay",
• title = "Iterative {Structure-Based} Genetic Programming for Neural Architecture Search",
• booktitle = "Proceedings of the 2023 Genetic and Evolutionary Computation Conference",
• year = "2023",
• editor = "Sara Silva and Luis Paquete and Leonardo Vanneschi and Nuno Lourenco and Ales Zamuda and Ahmed Kheiri and Arnaud Liefooghe and Bing Xue and Ying Bi and Nelishia Pillay and Irene Moser and Arthur Guijt and Jessica Catarino and Pablo Garcia-Sanchez and Leonardo Trujillo and Carla Silva and Nadarajen Veerapen",
• pages = "595--598",
• address = "Lisbon, Portugal",
• series = "GECCO '23",
• month = "15-19 " # jul,
• organisation = "SIGEVO",
• publisher = "Association for Computing Machinery",
• publisher_address = "New York, NY, USA",
• keywords = "genetic algorithms, genetic programming, neural architecture search, structured genetic programming: Poster",
• isbn13 = "9798400701191",
• DOI = "doi:10.1145/3583133.3590759",
• size = "4 pages",
• abstract = "In this paper we present an iterative structure-based genetic programming algorithm for neural architecture search. Canonical genetic programming uses a fitness function to determine where to move the search to in the program space. This research investigates using the structure of the syntax trees, representing different areas of the program space, in addition to the fitness function to direct the search. The structure is used to avoid areas of the search that previously led to local optima both globally (exploration) and locally (exploitation). The proposed approach is evaluated for image classification and video shorts creation. The iterative structure-based approach was found to produce better results then canonical genetic programming for both problem domains, with a slight reduction in computational cost. The approach also produced better results than genetic algorithms which are traditionally used for neural architecture search.",
• notes = "GECCO-2023 A Recombination of the 32nd International Conference on Genetic Algorithms (ICGA) and the 28th Annual Genetic Programming Conference (GP)",

}

Genetic Programming entries for Rahul Kapoor Nelishia Pillay

Citations