20 citations · 34 across the 4 of their papers we have counts for
7 papers
Natural language to SQL in low-code platforms
Sofia Aparicio, Samuel Arcadinho, João Nadkarni +5
One of the developers' biggest challenges in low-code platforms is retrieving data from a database using SQL queries. Here, we propose a pipeline allowing developers to write natur…
AutoLR: An Evolutionary Approach to Learning Rate Policies
Pedro Carvalho, Nuno Lourenço, Filipe Assunção +1
The choice of a proper learning rate is paramount for good Artificial Neural Network training and performance. In the past, one had to rely on experience and trial-and-error to fin…
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…
Automatic Design of Artificial Neural Networks for Gamma-Ray Detection
Filipe Assunção, João Correia, Rúben Conceição +4
The goal of this work is to investigate the possibility of improving current gamma/hadron discrimination based on their shower patterns recorded on the ground. To this end we propo…
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…