A Time Efficient Approach for Distributed Feature Selection Partitioning by Features. - Laura Moran-Fernandez; Verónica Bolón-Canedo; Amparo Alonso-Betanzos (CAEPIA, 2015)

An insight on complexity measures and classification in microarray data. - Verónica Bolón-Canedo; Laura Moran-Fernandez; Amparo Alonso-Betanzos (IJCNN, 2015)

Selection of the Best Base Classifier in One-Versus-One Using Data Complexity Measures. - Laura Morán-Fernández; Verónica Bolón-Canedo; Amparo Alonso-Betanzos (CAEPIA, 2016)

Data complexity measures for analyzing the effect of SMOTE over microarrays. - Laura Morán-Fernández; Verónica Bolón-Canedo; Amparo Alonso-Betanzos (ESANN, 2016)

A distributed approach for classification using distance metrics. - Laura Morán-Fernández; Verónica Bolón-Canedo; Amparo Alonso-Betanzos (ESANN, 2017)

Can classification performance be predicted by complexity measures? A study using microarray data. - Laura Moran-Fernandez; Verónica Bolón-Canedo; Amparo Alonso-Betanzos (Knowl. Inf. Syst., 2017)

Centralized vs. distributed feature selection methods based on data complexity measures. - Laura Moran-Fernandez; Verónica Bolón-Canedo; Amparo Alonso-Betanzos (Knowl. Based Syst., 2017)

On the use of different base classifiers in multiclass problems. - Laura Moran-Fernandez; Verónica Bolón-Canedo; Amparo Alonso-Betanzos (Prog. Artif. Intell., 2017)

Distributed classification based on distances between probability distributions in feature space. - Pablo Montero-Manso; Laura Morán-Fernández; Verónica Bolón-Canedo; José Antonio Vilar; Amparo Alonso-Betanzos (Inf. Sci., 2019)

Do we need hundreds of classifiers or a good feature selection? - Laura Morán-Fernández; Verónica Bolón-Canedo; Amparo Alonso-Betanzos (ESANN, 2020)

When Size Matters: Markov Blanket with Limited Bit Depth Conditional Mutual Information. - Laura Morán-Fernández; Eva Blanco-Mallo; Konstantinos Sechidis; Amparo Alonso-Betanzos; Verónica Bolón-Canedo (IoT Streams/ITEM@PKDD/ECML, 2020)

Feature selection with limited bit depth mutual information for portable embedded systems. - Laura Morán-Fernández; Konstantinos Sechidis; Verónica Bolón-Canedo; Amparo Alonso-Betanzos; Gavin Brown 001 (Knowl. Based Syst., 2020)

Dimensionality Reduction: Is Feature Selection More Effective Than Random Selection? - Laura Morán-Fernández; Verónica Bolón-Canedo (IWANN (1), 2021)

Feature Selection: From the Past to the Future. - Verónica Bolón-Canedo; Amparo Alonso-Betanzos; Laura Morán-Fernández; Brais Cancela (Advances in Selected Artificial Intelligence Areas, 2022)

Feature selection for transfer learning using particle swarm optimization and complexity measures. - Verónica Bolón-Canedo; Guillermo Castillo García; Laura Morán-Fernández (ESANN, 2022)

Less is more: Low-precision feature selection for wearables. - Samuel Suárez-Marcote; Laura Morán-Fernández; Verónica Bolón-Canedo (IJCNN, 2022)

Reduced precision discretization based on information theory. - Brais Ares; Laura Morán-Fernández; Verónica Bolón-Canedo (KES, 2022)

How important is data quality? Best classifiers vs best features. - Laura Morán-Fernández; Verónica Bolón-Canedo; Amparo Alonso-Betanzos (Neurocomputing, 2022)

Low-precision feature selection on microarray data: an information theoretic approach. - Laura Morán-Fernández; Verónica Bolón-Canedo; Amparo Alonso-Betanzos (Medical Biol. Eng. Comput., 2022)

Green Machine Learning. - Verónica Bolón-Canedo; Laura Morán-Fernández; Brais Cancela; Amparo Alonso-Betanzos (ESANN, 2023)

Efficient feature selection for domain adaptation using Mutual Information Maximization. - Guillermo Castillo García; Laura Morán-Fernández; Verónica Bolón-Canedo (ESANN, 2023)

Logarithmic division for green feature selection: an information-theoretic approach. - Samuel Suárez-Marcote; Laura Morán-Fernández; Verónica Bolón-Canedo (ESANN, 2023)

Feature selection for domain adaptation using complexity measures and swarm intelligence. - Guillermo Castillo García; Laura Morán-Fernández; Verónica Bolón-Canedo (Neurocomputing, 2023)

Machine Learning Methods for Predicting League of Legends Game Outcome. - Juan Agustín Hitar-García; Laura Morán-Fernández; Verónica Bolón-Canedo (IEEE Trans. Games, 2023)

Do all roads lead to Rome? Studying distance measures in the context of machine learning. - Eva Blanco-Mallo; Laura Morán-Fernández; Beatriz Remeseiro; Verónica Bolón-Canedo (Pattern Recognit., 2023)

Mutual Information-Based Feature Selection for Federated Learning Environments. - Samuel Suárez-Marcote; Laura Morán-Fernández; Verónica Bolón-Canedo (ICMLA, 2024)

A review of green artificial intelligence: Towards a more sustainable future. - Verónica Bolón-Canedo; Laura Morán-Fernández; Brais Cancela; Amparo Alonso-Betanzos (Neurocomputing, 2024)

CUDA acceleration of MI-based feature selection methods. - Bieito Beceiro; Jorge González-Domínguez; Laura Morán-Fernández; Verónica Bolón-Canedo; Juan Touriño (J. Parallel Distributed Comput., 2024)

Finding a needle in a haystack: insights on feature selection for classification tasks. - Laura Morán-Fernández; Verónica Bolón-Canedo (J. Intell. Inf. Syst., 2024)

Breaking boundaries: Low-precision conditional mutual information for efficient feature selection. - Laura Morán-Fernández; Eva Blanco-Mallo; Konstantinos Sechidis; Verónica Bolón-Canedo (Pattern Recognit., 2025)

ProgTutor: A Robotic-Based Framework to Support Teaching and Learning of Programming Fundamentals. - Javier Ortega-Morla; Antonio Leis; Alma Mallo; Laura Morán-Fernández; Sara Guerreiro-Santalla; Alejandro Paz-Lopez; Beatriz Pérez-Sánchez; Noelia Sánchez-Maroño; Alejandro Rodríguez-Arias; Oscar Fontenla-Romero; Francisco Bellas (IEEE Trans. Learn. Technol., 2025)

Optimising Resource Use Through Low-Precision Feature Selection: A Performance Analysis of Logarithmic Division and Stochastic Rounding. - Samuel Suárez-Marcote; Laura Morán-Fernández; Verónica Bolón-Canedo (Expert Syst. J. Knowl. Eng., 2025)