no code implementations • 29 Aug 2023 • Sofia Aparicio, Samuel Arcadinho, João Nadkarni, David Aparício, João Lages, Mariana Lourenço, Bartłomiej Matejczyk, Filipe Assunção
Alongside this, we describe the entire pipeline, which comprises a feedback loop that allows us to quickly collect production data and use it to retrain our SQL generation model.
no code implementations • 8 Jul 2020 • Pedro Carvalho, Nuno Lourenço, Filipe Assunção, Penousal Machado
This work presents AutoLR, a framework that evolves Learning Rate Schedulers for a specific Neural Network Architecture using Structured Grammatical Evolution.
1 code implementation • 1 Apr 2020 • Filipe Assunção, Nuno Lourenço, Bernardete Ribeiro, Penousal Machado
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, and the design and extraction of features, to the choice of the ML algorithm and its parameterisation.
1 code implementation • 1 Apr 2020 • Filipe Assunção, Nuno Lourenço, Bernardete Ribeiro, Penousal Machado
Despite aiding non-expert users to design and train ANNs, the vast majority of NE approaches disregard the knowledge that is gathered when solving other tasks, i. e., evolution starts from scratch for each problem, ultimately delaying the evolutionary process.
no code implementations • 9 May 2019 • Filipe Assunção, João Correia, Rúben Conceição, Mário Pimenta, Bernardo Tomé, Nuno Lourenço, Penousal Machado
The results show that the best CNN generated by Fast-DENSER++ improves by a factor of 2 when compared with the results reported by classic statistical approaches.
no code implementations • 8 May 2019 • Filipe Assunção, Nuno Lourenço, Penousal Machado, Bernardete Ribeiro
This paper proposes a new extension to Deep Evolutionary Network Structured Evolution (DENSER), called Fast-DENSER++ (F-DENSER++).
17 code implementations • 4 Jan 2018 • Filipe Assunção, Nuno Lourenço, Penousal Machado, Bernardete Ribeiro
Deep Evolutionary Network Structured Representation (DENSER) is a novel approach to automatically design Artificial Neural Networks (ANNs) using Evolutionary Computation.
no code implementations • 26 Jun 2017 • Filipe Assunção, Nuno Lourenço, Penousal Machado, Bernardete Ribeiro
On the other, there is no way to evolve networks with more than one output neuron.