“A review of green artificial intelligence: Towards a more sustainable future”, V. Bolón-Canedo, L. Morán-Fernández, B. Cancela & A. Alonso-Betanzos, Neurocomputing, vol. 596, 2024.

“Towards federated feature selection: Logarithmic division for resource-conscious methods”, S. Suárez-Marcote, L. Morán-Fernández, & V. Bolón-Canedo, Neurocomputing, vol. 596, 2024.

“Selección de características eficiente en entornos federados”, S. Suárez-Marcote, L. Morán-Fernández, & V. Bolón-Canedo, XX Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA), 2024.

“CUDA acceleration of MI-based feature selection methods”, B. Beceiro, J. González-Domínguez, L. Morán-Fernández, V. Bolón-Canedo, & J. Touriño, Journal of Parallel and Distributed Computing, 2024.

“Fed-mRMR: A lossless federated feature selection method”, J. Hermo,V. Bolón-Canedo, & S. Ladra, Information Science, 2024.

“Logarithmic division for green feature selection: an information-theoretic approach”, S. Suárez-Marcote, L. Morán-Fernández, & V. Bolón-Canedo, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), 2023.

“Efficient feature selection for domain adaptation using Mutual Information Maximization”, G. Castillo-García, L. Morán-Fernández, & V. Bolón-Canedo, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), 2023.

“Feature selection for domain adaptation using complexity measures and swarm intelligence”, G. Castillo-García, L. Morán-Fernández, & V. Bolón-Canedo, Neurocomputing, vol. 548, 2023.

“Fast Deep Autoencoder for Federated learning”, D. Novoa-Paradela, O. Romero-Fontenla, & B. Guijarro-Berdiñas, Pattern Recognition, 2023.