activity
20172023
most citedEvolving imputation strategies for missing data in classification problems with TPOT

10 citations · 14 across the 6 of their papers we have counts for

collaborators

6 papers

cs.NE2023

Neuroevolutionary algorithms driven by neuron coverage metrics for semi-supervised classification

Roberto Santana, Ivan Hidalgo-Cenalmor, Unai Garciarena +2

In some machine learning applications the availability of labeled instances for supervised classification is limited while unlabeled instances are abundant. Semi-supervised learnin…

cs.NE2021

Redefining Neural Architecture Search of Heterogeneous Multi-Network Models by Characterizing Variation Operators and Model Components

Unai Garciarena, Roberto Santana, Alexander Mendiburu

With neural architecture search methods gaining ground on manually designed deep neural networks -even more rapidly as model sophistication escalates-, the research trend shifts to…

cs.NE2021★ 1 cited

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…

cs.LG2019

Towards automatic construction of multi-network models for heterogeneous multi-task learning

Unai Garciarena, Alexander Mendiburu, Roberto Santana

Multi-task learning, as it is understood nowadays, consists of using one single model to carry out several similar tasks. From classifying hand-written characters of different alph…

cs.LG2018★ 3 cited

Towards a more efficient representation of imputation operators in TPOT

Unai Garciarena, Alexander Mendiburu, Roberto Santana

Automated Machine Learning encompasses a set of meta-algorithms intended to design and apply machine learning techniques (e.g., model selection, hyperparameter tuning, model assess…

cs.LG2017★ 10 cited

Evolving imputation strategies for missing data in classification problems with TPOT

Unai Garciarena, Roberto Santana, Alexander Mendiburu

Missing data has a ubiquitous presence in real-life applications of machine learning techniques. Imputation methods are algorithms conceived for restoring missing values in the dat…