Titlebook: Genetic Programming; 21st European Confer Mauro Castelli,Lukas Sekanina,Pablo García-Sánchez Conference proceedings 2018 Springer Internati

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Evolving the Topology of Large Scale Deep Neural Networks. Most of the success in these tasks is merit of Convolutional Neural Networks (CNNs), which allow the automatic construction of features. However, designing such networks is not an easy task, which requires expertise and insight. In this paper we introduce DENSER, a novel representation for the evo

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Analyzing Feature Importance for Metabolomics Using Genetic Programmingsses related to how the human body responds to genetic and environmental perturbations. Considering the complexity of metabolism, metabolites and their represented cellular processes can correlate and synergistically contribute to a phenotypic status. Genetic programming (GP) provides advanced analy

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Multi-level Grammar Genetic Programming for Scheduling in Heterogeneous Networksr, it requires from these entities to implement an effective scheduling algorithm. The state-of-the-art for the scheduling in Heterogeneous Networks is a Grammar-Guided Genetic Programming algorithm which evolves, from a given grammar, an expression that maps to the scheduling of transmissions. We e

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