Search Results for author: Gisele L. Pappa

Found 9 papers, 4 papers with code

Metaheuristics "In the Large"

no code implementations19 Nov 2020 Jerry Swan, Steven Adriaensen, Alexander E. I. Brownlee, Kevin Hammond, Colin G. Johnson, Ahmed Kheiri, Faustyna Krawiec, J. J. Merelo, Leandro L. Minku, Ender Özcan, Gisele L. Pappa, Pablo García-Sánchez, Kenneth Sörensen, Stefan Voß, Markus Wagner, David R. White

We describe our vision and report on progress, showing how the adoption of common protocols for all metaheuristics can help liberate the potential of the field, easing the exploration of the design space of metaheuristics.

Neural Architecture Search in Graph Neural Networks

1 code implementation31 Jul 2020 Matheus Nunes, Gisele L. Pappa

However, they possess a large number of hyperparameters and their design and optimization is currently hand-made, based on heuristics or empirical intuition.

Evolutionary Algorithms Neural Architecture Search

A Robust Experimental Evaluation of Automated Multi-Label Classification Methods

1 code implementation16 May 2020 Alex G. C. de Sá, Cristiano G. Pimenta, Gisele L. Pappa, Alex A. Freitas

In this work, we provide a general comparison of five automated multi-label classification methods -- two evolutionary methods, one Bayesian optimization method, one random search and one greedy search -- on 14 datasets and three designed search spaces.

AutoML Bayesian Optimization +3

Multi-label classification search space in the MEKA software

1 code implementation28 Nov 2018 Alex G. C. de Sá, Cristiano G. Pimenta, Gisele L. Pappa, Alex A. Freitas

This supplementary material aims to describe the proposed multi-label classification (MLC) search spaces based on the MEKA and WEKA softwares.

Classification General Classification +1

Solving the Exponential Growth of Symbolic Regression Trees in Geometric Semantic Genetic Programming

1 code implementation18 Apr 2018 Joao Francisco B. S. Martins, Luiz Otavio V. B. Oliveira, Luis F. Miranda, Felipe Casadei, Gisele L. Pappa

Advances in Geometric Semantic Genetic Programming (GSGP) have shown that this variant of Genetic Programming (GP) reaches better results than its predecessor for supervised machine learning problems, particularly in the task of symbolic regression.

regression Symbolic Regression

How Noisy Data Affects Geometric Semantic Genetic Programming

no code implementations4 Jul 2017 Luis F. Miranda, Luiz Otavio V. B. Oliveira, Joao Francisco B. S. Martins, Gisele L. Pappa

The results show that, as we increase the percentage of noisy instances, the generalization performance degradation is more pronounced in GSGP than GP.

Selective Harvesting over Networks

no code implementations15 Mar 2017 Fabricio Murai, Diogo Rennó, Bruno Ribeiro, Gisele L. Pappa, Don Towsley, Krista Gile

We find that it is possible to collect a much larger set of targets by using multiple classifiers, not by combining their predictions as an ensemble, but switching between classifiers used at each step, as a way to ease the tunnel vision effect.

Multi-Armed Bandits

The Effect of Social Feedback in a Reddit Weight Loss Community

no code implementations25 Feb 2016 Tiago O. Cunha, Ingmar Weber, Hamed Haddadi, Gisele L. Pappa

It is generally accepted as common wisdom that receiving social feedback is helpful to (i) keep an individual engaged with a community and to (ii) facilitate an individual's positive behavior change.

Social and Information Networks

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