Publications
“Abrirás una revista y me encontrarás a mí
debo ser algo payaso pero eso me hace feliz”
Rock and Roll Star, Loquillo, 1980
2024
Clara Álvarez-Rodríguez, Emilio Parrado-Hernández, Jorge Pérez-Aracil, Luis Prieto-Godino, Sancho Salcedo-Sanz. 2024. “Interpretable extreme wind speed prediction with concept bottleneck models.” Renewable Energy 231, 120935
Carlos Sevilla-Salcedo, Ascensión Gallardo-Antolín, Vanessa Gómez-Verdejo, Emilio Parrado-Hernández. 2024. “Bayesian learning of feature spaces for multitask regression.” Neural Networks 179, 106619
2023
Vanessa Gómez-Verdejo, Emilio Parrado-Hernández, Manel Martínez-Ramón. 2023. “Adaptive sparse gaussian process.” IEEE Transactions on Neural Networks and Learning Systems
M.C. Bravo, R. Jiménez, E. Parrado-Hernández, J.J. Fernández and A. Pellicer. 2024. “Predicting effectiveness of drugs used for treating cardiovascular conditions in newborn infants.” Pediatric Research 95(4), pp. 1124–1131
2019
Vanessa Gomez-Verdejo, Emilio Parrado-Hernandez, and Jussi Tohka. 2019. “Sign-Consistency Based Variable Importance for Machine Learning in Brain Imaging.” Neuroinformatics 17 (4): 593–609.
2018
Parrado-Hernández, Emilio, Guillermo Robles, Jorge Alfredo Ardila-Rey, and Juan Manuel Martı́nez-Tarifa. 2018. “Robust Condition Assessment of Electrical Equipment with One Class Support Vector Machines Based on the Measurement of Partial Discharges.” Energies 11 (3): 486.
Robles, Guillermo, José Manuel Fresno, Juan Manuel Martı́nez-Tarifa, Jorge Alfredo Ardila-Rey, and Emilio Parrado-Hernández. 2018. “Partial Discharge Spectral Characterization in HF, VHF and UHF Bands Using Particle Swarm Optimization.” Sensors 18 (3): 746.
Rivasplata, Omar, Emilio Parrado-Hernández, John S Shawe-Taylor, Shiliang Sun, and Csaba Szepesvári. 2018. “PAC-Bayes Bounds for Stable Algorithms with Instance-Dependent Priors.” In Advances in Neural Information Processing Systems, 9214–24.
2017
Muñoz-Romero, Sergio, Vanessa Gómez-Verdejo, and Emilio Parrado-Hernández. 2017. “A Novel Framework for Parsimonious Multivariate Analysis.” Pattern Recognition 71: 173–86.
Boya, Carlos, Guillermo Robles, Emilio Parrado-Hernández, and Marta Ruiz-Llata. 2017. “Detection of Partial Discharge Sources Using UHF Sensors and Blind Signal Separation.” Sensors 17 (11): 2625.
2016
Robles, Guillermo, Emilio Parrado-Hernández, Jorge Ardila-Rey, and Juan Manuel Martı́nez-Tarifa. 2016. “Multiple Partial Discharge Source Discrimination with Multiclass Support Vector Machines.” Expert Systems with Applications 55: 417–28.
2014
Parrado-Hernández, Emilio, Vanessa Gómez-Verdejo, Manel Martı́nez-Ramón, John Shawe-Taylor, Pino Alonso, Jesús Pujol, José M Menchón, Narcis Cardoner, and Carles Soriano-Mas. 2014. “Discovering Brain Regions Relevant to Obsessive–Compulsive Disorder Identification Through Bagging and Transduction.” Medical Image Analysis 18 (3): 435–48.
2012
Parrado-Hernández, Emilio, Amiran Ambroladze, John Shawe-Taylor, and Shiliang Sun. 2012. “PAC-Bayes Bounds with Data Dependent Priors.” The Journal of Machine Learning Research 13 (1): 3507–31.
Lazaro-Gredilla, Miguel, Vanessa Gomez-Verdejo, and Emilio Parrado-Hernández. 2012. “Low-Cost Model Selection for SVMs Using Local Features.” Engineering Applications of Artificial Intelligence 25 (6): 1203–11.
Parrado-Hernandez, Emilio, Vanessa Gomez-Verdejo, Manel Martinez-Ramon, John Shawe-Taylor, Pino Alonso, Jesús Pujol, José M Menchón, Narcı́s Cardoner, and Carles Soriano-Mas. 2012. “Voxel Selection in MRI Through Bagging and Conformal Analysis: Application to Detection of Obsessive Compulsive Disorder.” In 2012 Second International Workshop on Pattern Recognition in NeuroImaging, 49–52. IEEE.
2011
Garcı́a-Garcı́a, Darı́o, Emilio Parrado-Hernández, and Fernando Diaz-de-Maria. 2011. “State-Space Dynamics Distance for Clustering Sequential Data.” Pattern Recognition 44 (5): 1014–22.
2010
Garcı́a-Garcı́a, Darı́o, Jerónimo Arenas-Garcı́a, Emilio Parrado-Hernández, and Fernando Diaz-de-Maria. 2010. “Music Genre Classification Using the Temporal Structure of Songs.” In 2010 IEEE International Workshop on Machine Learning for Signal Processing, 266–71. IEEE.
2008
Garcı́a-Garcı́a, Darı́o, Emilio Parrado Hernández, and Fernando Dı́az-de Marı́a. 2008. “A New Distance Measure for Model-Based Sequence Clustering.” IEEE Transactions on Pattern Analysis & Machine Intelligence, no. 7: 1325–31.
2007
Ambroladze, Amiran, Emilio Parrado-Hernández, and John Shawe-Taylor. 2007a. “Complexity of Pattern Classes and the Lipschitz Property.” Theoretical Computer Science 382 (3): 232–46.
Ambroladze, Amiran, Emilio Parrado-Hernández, and John Shawe-Taylor. 2007b. “Tighter PAC-Bayes Bounds.” Advances in Neural Information Processing Systems 19: 9.
2006
Navia-Vázquez, A, and E Parrado-Hernández. 2006. “Support Vector Machine Interpretation.” Neurocomputing 69 (13): 1754–59.
Navia-Vázquez, Angel, D Gutierrez-Gonzalez, Emilio Parrado-Hernández, and JJ Navarro-Abellan. 2006. “Distributed Support Vector Machines.” IEEE Transactions on Neural Networks 17 (4): 1091–97.
Bennett, Kristin P, and Emilio Parrado-Hernández. 2006. “The Interplay of Optimization and Machine Learning Research.” The Journal of Machine Learning Research 7: 1265–81.
2003
Parrado-Hernández, Emilio, I Mora-Jiménez, Jeronimo Arenas-Garcıa, Anı́bal R Figueiras-Vidal, and Angel Navia-Vázquez. 2003. “Growing Support Vector Classifiers with Controlled Complexity.” Pattern Recognition 36 (7): 1479–88.
Parrado-Hernández, Emilio, Eduardo Gómez-Sánchez, and Yannis A Dimitriadis. 2003. “Study of Distributed Learning as a Solution to Category Proliferation in Fuzzy ARTMAP Based Neural Systems.” Neural Networks 16 (7): 1039–57.
Parrado-Hernández, Emilio, J Arenas-Garcıa, Inma Mora-Jiménez, and Angel Navia-Vázquez. 2003. “On Problem-Oriented Kernel Refining.” Neurocomputing 55 (1): 135–50.