105 citations · 282 across the 25 of their papers we have counts for
30 papers
GreenFactory: Ensembling Zero-Cost Proxies to Estimate Performance of Neural Networks
Gabriel Cortês, Nuno Lourenço, Paolo Romano +1
Determining the performance of a Deep Neural Network during Neural Architecture Search processes is essential for identifying optimal architectures and hyperparameters. Traditional…
On the Dynamics of Mating Preferences in Genetic Programming
José Maria Simões, Nuno Lourenço, Penousal Machado
Several mating restriction techniques have been implemented in Evolutionary Algorithms to promote diversity. From similarity-based selection to niche preservation, the general goal…
GreenMachine: Automatic Design of Zero-Cost Proxies for Energy-Efficient NAS
Gabriel Cortês, Nuno Lourenço, Penousal Machado
Artificial Intelligence (AI) has driven innovations and created new opportunities across various sectors. However, leveraging domain-specific knowledge often requires automated too…
Towards Physical Plausibility in Neuroevolution Systems
Gabriel Cortês, Nuno Lourenço, Penousal Machado
The increasing usage of Artificial Intelligence (AI) models, especially Deep Neural Networks (DNNs), is increasing the power consumption during training and inference, posing envir…
SPENSER: Towards a NeuroEvolutionary Approach for Convolutional Spiking Neural Networks
Henrique Branquinho, Nuno Lourenço, Ernesto Costa
Spiking Neural Networks (SNNs) have attracted recent interest due to their energy efficiency and biological plausibility. However, the performance of SNNs still lags behind traditi…
Reducing the Price of Stable Cable Stayed Bridges with CMA-ES
Gabriel Fernandes, Nuno Lourenço, João Correia
The design of cable-stayed bridges requires the determination of several design variables' values. Civil engineers usually perform this task by hand as an iteration of steps that s…
Automatic Design of Telecom Networks with Genetic Algorithms
João Correia, Gustavo Gama, João Tiago Guerrinha +4
With the increasing demand for high-quality internet services, deploying GPON/Fiber-to-the-Home networks is one of the biggest challenges that internet providers have to deal with…
All You Need Is Sex for Diversity
José Maria Simões, Nuno Lourenço, Penousal Machado
Maintaining genetic diversity as a means to avoid premature convergence is critical in Genetic Programming. Several approaches have been proposed to achieve this, with some focusin…
Context Matters: Adaptive Mutation for Grammars
Pedro Carvalho, Jessica Mégane, Nuno Lourenço +1
This work proposes Adaptive Facilitated Mutation, a self-adaptive mutation method for Structured Grammatical Evolution (SGE), biologically inspired by the theory of facilitated var…
Structured mutation inspired by evolutionary theory enriches population performance and diversity
Stefano Tiso, Pedro Carvalho, Nuno Lourenço +1
Grammar-Guided Genetic Programming (GGGP) employs a variety of insights from evolutionary theory to autonomously design solutions for a given task. Recent insights from evolutionar…
Adversarial Robustness Assessment of NeuroEvolution Approaches
Inês Valentim, Nuno Lourenço, Nuno Antunes
NeuroEvolution automates the generation of Artificial Neural Networks through the application of techniques from Evolutionary Computation. The main goal of these approaches is to b…
Exploring Generative Adversarial Networks for Text-to-Image Generation with Evolution Strategies
Victor Costa, Nuno Lourenço, João Correia +1
In the context of generative models, text-to-image generation achieved impressive results in recent years. Models using different approaches were proposed and trained in huge datas…
Probabilistic Structured Grammatical Evolution
Jessica Mégane, Nuno Lourenço, Penousal Machado
The grammars used in grammar-based Genetic Programming (GP) methods have a significant impact on the quality of the solutions generated since they define the search space by restri…
Co-evolutionary Probabilistic Structured Grammatical Evolution
Jessica Mégane, Nuno Lourenço, Penousal Machado
This work proposes an extension to Structured Grammatical Evolution (SGE) called Co-evolutionary Probabilistic Structured Grammatical Evolution (Co-PSGE). In Co-PSGE each individua…
On the Exploitation of Neuroevolutionary Information: Analyzing the Past for a More Efficient Future
Unai Garciarena, Nuno Lourenço, Penousal Machado +2
Neuroevolutionary algorithms, automatic searches of neural network structures by means of evolutionary techniques, are computationally costly procedures. In spite of this, due to t…
Evolving Learning Rate Optimizers for Deep Neural Networks
Pedro Carvalho, Nuno Lourenço, Penousal Machado
Artificial Neural Networks (ANNs) became popular due to their successful application difficult problems such image and speech recognition. However, when practitioners want to desig…
Probabilistic Grammatical Evolution
Jessica Mégane, Nuno Lourenço, Penousal Machado
Grammatical Evolution (GE) is one of the most popular Genetic Programming (GP) variants, and it has been used with success in several problem domains. Since the original proposal,…
Demonstrating the Evolution of GANs through t-SNE
Victor Costa, Nuno Lourenço, João Correia +1
Generative Adversarial Networks (GANs) are powerful generative models that achieved strong results, mainly in the image domain. However, the training of GANs is not trivial, presen…
Exploring the Evolution of GANs through Quality Diversity
Victor Costa, Nuno Lourenço, João Correia +1
Generative adversarial networks (GANs) achieved relevant advances in the field of generative algorithms, presenting high-quality results mainly in the context of images. However, G…
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…
Using Skill Rating as Fitness on the Evolution of GANs
Victor Costa, Nuno Lourenço, João Correia +1
Generative Adversarial Networks (GANs) are an adversarial model that achieved impressive results on generative tasks. In spite of the relevant results, GANs present some challenges…
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…
COEGAN: Evaluating the Coevolution Effect in Generative Adversarial Networks
Victor Costa, Nuno Lourenço, João Correia +1
Generative adversarial networks (GAN) present state-of-the-art results in the generation of samples following the distribution of the input dataset. However, GANs are difficult to…