Multithreaded and Spark parallelization of feature selection filters. - Carlos Eiras-Franco; Verónica Bolón-Canedo; Sabela Ramos; Jorge González-Domínguez; Amparo Alonso-Betanzos; Juan Touriño (J. Comput. Sci., 2016)

Scalable approximate k-NN Graph construction based on Locality Sensitive Hashing. - Carlos Eiras-Franco; Leslie Kanthan; Amparo Alonso-Betanzos; David Martínez-Rego (ESANN, 2017)

Case Study of Anomaly Detection and Quality Control of Energy Efficiency and Hygrothermal Comfort in Buildings. - Carlos Eiras-Franco; Miguel Flores; Verónica Bolón-Canedo; Sonia Zaragoza; Rubén Fernández-Casal; Salvador Naya; Javier Tarrío-Saavedra (DATA, 2019)

A scalable decision-tree-based method to explain interactions in dyadic data. - Carlos Eiras-Franco; Bertha Guijarro-Berdiñas; Amparo Alonso-Betanzos; Antonio Bahamonde (Decis. Support Syst., 2019)

Large scale anomaly detection in mixed numerical and categorical input spaces. - Carlos Eiras-Franco; David Martínez-Rego; Bertha Guijarro-Berdiñas; Amparo Alonso-Betanzos; Antonio Bahamonde (Inf. Sci., 2019)

Fast Distributed kNN Graph Construction Using Auto-tuned Locality-sensitive Hashing. - Carlos Eiras-Franco; David Martínez-Rego; Leslie Kanthan; César Piñeiro; Antonio Bahamonde; Bertha Guijarro-Berdiñas; Amparo Alonso-Betanzos (ACM Trans. Intell. Syst. Technol., 2020)

Scalable feature selection using ReliefF aided by locality-sensitive hashing. - Carlos Eiras-Franco; Bertha Guijarro-Berdiñas; Amparo Alonso-Betanzos; Antonio Bahamonde (Int. J. Intell. Syst., 2021)

Sustainable Personalisation and Explainability in Dyadic Data Systems. - Jorge Paz-Ruza; Carlos Eiras-Franco; Bertha Guijarro-Berdiñas; Amparo Alonso-Betanzos (KES, 2022)

Explanation Method for Anomaly Detection on Mixed Numerical and Categorical Spaces. - Iñigo López-Riobóo Botana; Carlos Eiras-Franco; Julio C. Hernandez-Castro; Amparo Alonso-Betanzos (CoRR, 2022)

Fast anomaly detection with locality-sensitive hashing and hyperparameter autotuning. - Jorge Meira; Carlos Eiras-Franco; Verónica Bolón-Canedo; Goreti Marreiros; Amparo Alonso-Betanzos (Inf. Sci., 2022)

Beyond RMSE and MAE: Introducing EAUC to unmask hidden bias and unfairness in dyadic regression models. - Jorge Paz-Ruza; Amparo Alonso-Betanzos; Bertha Guijarro-Berdiñas; Brais Cancela; Carlos Eiras-Franco (CoRR, 2024)

Sustainable transparency on recommender systems: Bayesian ranking of images for explainability. - Jorge Paz-Ruza; Amparo Alonso-Betanzos; Bertha Guijarro-Berdiñas; Brais Cancela; Carlos Eiras-Franco (Inf. Fusion, 2024)

A novel framework for generic Spark workload characterization and similar pattern recognition using machine learning. - Mariano Garralda-Barrio; Carlos Eiras-Franco; Verónica Bolón-Canedo (J. Parallel Distributed Comput., 2024)

Evaluate with the Inverse: Efficient Approximation of Latent Explanation Quality Distribution. - Carlos Eiras-Franco; Anna Hedström; Marina M.-C. Höhne (AAAI, 2025)

Performance and sustainability of BERT derivatives in dyadic data. - Miguel Escarda; Carlos Eiras-Franco; Brais Cancela; Bertha Guijarro-Berdiñas; Amparo Alonso-Betanzos (Expert Syst. Appl., 2025)

Adaptive incremental transfer learning for efficient performance modeling of big data workloads. - Mariano Garralda-Barrio; Carlos Eiras-Franco; Verónica Bolón-Canedo (Future Gener. Comput. Syst., 2025)

Predictively Combatting Toxicity in Health-related Online Discussions through Machine Learning. - Jorge Paz-Ruza; Amparo Alonso-Betanzos; Bertha Guijarro-Berdiñas; Carlos Eiras-Franco (CoRR, 2025)