Francisco Herrera

Herrera, F., García, S., del Jesus Díaz, M. J., Sánchez, L., & de Prado, M. L. (2026). Co-Explainers: A Position on Interactive XAI for Human–AI Collaboration as a Harm-Mitigation Infrastructure. Machine Learning and Knowledge Extraction, 8. https://doi.org/10.3390/make8030069

Charte, D. ", Charte Ojeda, F., & Herrera, F. (2021). Reducing Data Complexity using Autoencoders with Class-informed Loss Functions. IEEE Transactions on Pattern Analysis and Machine Intelligence, In Press. https://doi.org/10.1109/TPAMI.2021.3127698

Charte, D. ", Sevillano-García, I., Lucena-González, M. J., Martín-Rodríguez, J. L., Charte Ojeda, F., & Herrera, F. (2021). Slicer: Feature Learning for Class Separability with Least-Squares Support Vector Machine Loss and COVID-19 Chest X-Ray Case Study. En H. S. González, I. P. López, P. G. Bringas, H. Quintián, & E. Corchado (Eds.), Hybrid Artificial Intelligent Systems (HAIS 2021) (pp. 305-315). Cham: Springer International Publishing.

Herrera, F., Carmona, C. J., González, P., & del Jesus Díaz, M. J. (2011). An overview on subgroup discovery: Foundations and applications. Knowledge and Information Systems, 29, 495-525. https://doi.org/10.1007/s10115-010-0356-2 (Original work published)