52 citations · 84 across the 6 of their papers we have counts for
4 papers · 1 filter
Evolution of Scikit-Learn Pipelines with Dynamic Structured Grammatical Evolution
Filipe Assunção, Nuno Lourenço, Bernardete Ribeiro +1
The deployment of Machine Learning (ML) models is a difficult and time-consuming job that comprises a series of sequential and correlated tasks that go from the data pre-processing…
Incremental Evolution and Development of Deep Artificial Neural Networks
Filipe Assunção, Nuno Lourenço, Bernardete Ribeiro +1
NeuroEvolution (NE) methods are known for applying Evolutionary Computation to the optimisation of Artificial Neural Networks(ANNs). Despite aiding non-expert users to design and t…
Fast-DENSER++: Evolving Fully-Trained Deep Artificial Neural Networks
Filipe Assunção, Nuno Lourenço, Penousal Machado +1
This paper proposes a new extension to Deep Evolutionary Network Structured Evolution (DENSER), called Fast-DENSER++ (F-DENSER++). The vast majority of NeuroEvolution methods that…
Towards the Evolution of Multi-Layered Neural Networks: A Dynamic Structured Grammatical Evolution Approach
Filipe Assunção, Nuno Lourenço, Penousal Machado +1
Current grammar-based NeuroEvolution approaches have several shortcomings. On the one hand, they do not allow the generation of Artificial Neural Networks (ANNs composed of more th…