Postdoctoral researcher
Universidade da Coruña
Research topics
Scalable machine learning
Explainable machine learning
I am a postdoctoral researcher at Universidade da Coruña. As a member of the LIDIA Group I work on obtaining scalable and explainable machine learning algorithms. I am absolutely fascinated with the possibility of designing intelligent machines and by the study of intelligence itself.
Google Scholar - Research Gate - Github - Twitter - ORCID
Performance and Sustainability of Bert Derivatives in Dyadic Data Escarda Fernández, M., Eiras-Franco, C., Cancela, B., Alonso-Betanzos, A., & Guijarro-Berdiñas, B. Performance and Sustainability of Bert Derivatives in Dyadic Data. Expert Systems With Applications, 2024. - [https://doi.org/10.1016/j.eswa.2024.125647]
Adaptive Incremental Transfer Learning for Efficient Performance Modeling of Big Data Workload Garralda-Barrio, M., Eiras-Franco, C., & Bolón-Canedo, V. Adaptive Incremental Transfer Learning for Efficient Performance Modeling of Big Data Workloads. Journal of Parallel and Distributed Computing, 2024. - [https://dx.doi.org/10.2139/ssrn.4987186]
Sustainable transparency on recommender systems: Bayesian ranking of images for explainability Paz-Ruza, J., Alonso-Betanzos, A., Guijarro-Berdiñas, B., Cancela-Barizo, B., C., (2024). Sustainable transparency on recommender systems: Bayesian ranking of images for explainability. Information Fusion, 2024 - [https://doi.org/10.1016/j.inffus.2024.102497]
A novel framework for generic Spark workload characterization and similar pattern recognition using machine learning Garralda-Barrio, M., Eiras-Franco, C., Bolón-Canedo, V., (2024). A novel framework for generic Spark workload characterization and similar pattern recognition using machine learning. Jornal of Parallel and Distributed Computing, 2024 - [https://doi.org/10.1016/j.jpdc.2024.104881]
Explanation Method for Anomaly Detection on Mixed Numerical and Categorical Spaces López-Riobóo Botana, I., Eiras-Franco, C., Hernández-Castro, J., Alonso-Betanzos, A., (2022). Explanation Method for Anomaly Detection on Mixed Numerical and Categorical Spaces. arxiv preprint, 2022 - [preprint]
Fast Anomaly Detection with Locality-Sensitive Hashing and Hyperparameter AutoTuning Meira, J., Eiras-Franco, C., Bolón-Canedo, V., Marreiros, G., Alonso-Betanzos, A., (2022). Fast Anomaly Detection with Locality-Sensitive Hashing and Hyperparameter AutoTuning. Information Sciences, 2022 - [https://doi.org/10.1016/j.ins.2022.06.035] [preprint]
Scalable feature selection using ReliefF aided by locality-sensitive hashing. Eiras-Franco, C., Guijarro-Berdiñas, B., Alonso-Betanzos, A., & Bahamonde, A., (2020). Scalable feature selection using ReliefF aided by locality-sensitive hashing. International Journal of Intelligent Systems and Technology (IJIS), 2021 - [https://doi.org/10.1002/int.22546]
New scalable machine learning methods: Beyond classification and regression. Eiras-Franco, C., Guijarro-Berdiñas, B., Alonso-Betanzos, A., & Bahamonde, A. Doctoral thesis. - [Manuscript]
Fast Distributed kNN Graph Construction Using Auto-tuned Locality-sensitive Hashing. Eiras-Franco, C., Martínez-Rego, D., Kanthan, L., Piñeiro, C., Bahamonde, A., Guijarro-Berdiñas, B., & Alonso-Betanzos, A. (2020). Fast Distributed k NN Graph Construction Using Auto-tuned Locality-sensitive Hashing. ACM Transactions on Intelligent Systems and Technology (TIST), 11(6), 1-18. - [https://doi.org/10.1145/3408889] [preprint]
Large Scale Anomaly Detection in Mixed Numerical and Categorical Input Spaces. Eiras-Franco, C., Martínez-Rego, D., Guijarro-Berdiñas, B., Alonso-Betanzos, A., & Bahamonde, A. Information Sciences, 487, 115-127. - [https://doi.org/10.1016/j.ins.2019.03.013] [preprint]
Case Study of Anomaly Detection and Quality Control of Energy Efficiency and Hygrothermal Comfort in Buildings. Eiras-Franco, C., Flores, M., Bolón-Canedo, V., Zaragoza, S., Fernández-Casal, R., Naya, S., & Tarrıo-Saavedra, J. In Proceedings of the 8th International Conference on Data Science, Technology and Applications (DATA 2019) - [Conference] [preprint]
A scalable decision-tree-based method to explain interactions in dyadic data. Eiras-Franco, C., Guijarro-Berdiñas, B., Alonso-Betanzos, A., & Bahamonde, A. Decision Support Systems, 127, 113141. - [https://doi.org/10.1016/j.dss.2019.113141] [preprint]
Preprocessing in High Dimensional Datasets. Alonso-Betanzos, A., Bolón-Canedo, V., Eiras-Franco, C., Morán-Fernández, L., & Seijo-Pardo, B. In Advances in Biomedical Informatics (pp. 247-271). Springer, Cham. - [https://doi.org/10.1007/978-3-319-67513-8_11]
Scalable approximate kNN Graph construction based on Locality Sensitive Hashing. Eiras-Franco, C., Kanthan, L., Alonso-Betanzos, A., & Martínez-Rego, D. (2017). Scalable approximate k-NN Graph construction based on Locality Sensitive Hashing. In 25th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - Proceedings - [Manuscript]
Multithreaded and Spark parallelization of feature selection filters. Eiras-Franco, C., Bolón-Canedo, V., Ramos, S., González-Domínguez, J., Alonso-Betanzos, A., & Tourino, J. Journal of Computational Science, 17, 609-619. - [https://doi.org/10.1016/j.jocs.2016.07.002] [preprint]