Emilio Parrado-Hernández

发表

Low-cost model selection for SVMs using local features

Miguel Lázaro-Gredilla, Vanessa Gómez-Verdejo, Emilio Parrado-Hernández, 2012, Eng. Appl. Artif. Intell..

Automatic Design of Neuromarkers for OCD Characterization

Manel Martínez-Ramón, Vanessa Gómez-Verdejo, Emilio Parrado-Hernández, 2014, ECML/PKDD.

Partial Discharge Spectral Characterization in HF, VHF and UHF Bands Using Particle Swarm Optimization

Guillermo Robles, Emilio Parrado-Hernández, José Manuel Fresno, 2018, Sensors.

Interference-aware MIMO precoder design with realistic power constraints

Matilde Sánchez Fernández, Ana García Armada, Emilio Parrado-Hernández, 2013, 2013 IEEE International Conference on Communications Workshops (ICC).

On problem-oriented kernel refining

I. Mora-Jiménez, Emilio Parrado-Hernández, Ángel Navia-Vázquez, 2003, Neurocomputing.

State-space dynamics distance for clustering sequential data

Emilio Parrado-Hernández, Fernando Díaz-de-María, Dario García-García, 2010, Pattern Recognit..

Identification of OCD-Relevant Brain Areas through Multivariate Feature Selection

Manel Martínez-Ramón, Vanessa Gómez-Verdejo, Emilio Parrado-Hernández, 2011, MLINI.

PAC-bayes bounds with data dependent priors

Shiliang Sun, Amiran Ambroladze, John Shawe-Taylor, 2012, J. Mach. Learn. Res..

Music Genre Classification based on Dynamical Models

Alberto García-Durán, Emilio Parrado-Hernández, Jerónimo Arenas-García, 2012, ICPRAM.

A novel framework for parsimonious multivariate analysis

Vanessa Gómez-Verdejo, Emilio Parrado-Hernández, Sergio Muñoz-Romero, 2017, Pattern Recognit..

SVM-based lost packets concealment for ASR applications over IP

Carmen Peláez-Moreno, Emilio Parrado-Hernández, Fernando Díaz-de-María, 2002, 2002 11th European Signal Processing Conference.

Study of distributed learning as a solution to category proliferation in Fuzzy ARTMAP based neural systems

Yannis A. Dimitriadis, Eduardo Gómez-Sánchez, Emilio Parrado-Hernández, 2003, Neural Networks.

The Interplay of Optimization and Machine Learning Research

Kristin P. Bennett, Emilio Parrado-Hernández, E. Parrado-Hernández, 2006, J. Mach. Learn. Res..

Growing support vector classifiers with controlled complexity

Aníbal R. Figueiras-Vidal, I. Mora-Jiménez, Emilio Parrado-Hernández, 2003, Pattern Recognit..

CDMA satellite capacity dynamics and efficiency with imperfect power control for simultaneous QoS classes and diversity

Maria Angeles Vázquez-Castro, Fernando Pérez-Fontán, Emilio Parrado-Hernández, 2002, Vehicular Technology Conference. IEEE 55th Vehicular Technology Conference. VTC Spring 2002 (Cat. No.02CH37367).

CDMA satellite capacity dynamics with imperfect power control for simultaneous QoS classes

Maria Angeles Vázquez-Castro, Emilio Parrado-Hernández, D. Belay-Zeleke, 2002, Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE.

Multi-kernel Growing Support Vector Regressor

Emilio Parrado-Hernández, Ángel Navia-Vázquez, D. Gutiérrez-González, 2005, IWANN.

Classifier-based affinities for clustering sets of vectors

Raúl Santos-Rodríguez, Emilio Parrado-Hernández, Dario García-García, 2012, 2012 IEEE International Workshop on Machine Learning for Signal Processing.

An Application of SVM to Lost Packets Reconstruction in Voice-Enabled Services

Carmen Peláez-Moreno, Emilio Parrado-Hernández, Fernando Díaz-de-María, 2002, ICANN.

A New Distance Measure for Model-Based Sequence Clustering

Emilio Parrado-Hernández, Fernando Díaz-de-María, Dario García-García, 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Tighter PAC-Bayes Bounds

John Shawe-Taylor, Amiran Ambroladze, Emilio Parrado-Hernández, 2006, NIPS.

Detection of Partial Discharge Sources Using UHF Sensors and Blind Signal Separation

Guillermo Robles, Emilio Parrado-Hernández, Marta Ruiz-Llata, 2017, Sensors.

Voxel Selection in MRI through Bagging and Conformal Analysis: Application to Detection of Obsessive Compulsive Disorder

John Shawe-Taylor, Manel Martínez-Ramón, Vanessa Gómez-Verdejo, 2012, 2012 Second International Workshop on Pattern Recognition in NeuroImaging.

Sign-Consistency Based Variable Importance for Machine Learning in Brain Imaging

Jussi Tohka, Vanessa Gómez-Verdejo, Emilio Parrado-Hernández, 2017, Neuroinformatics.

Sign-consistency based variable importance for machine learning in brain imaging

Vanessa Gómez-Verdejo, Emilio Parrado-Hernández, Jussi Tohka, 2017 .

Robust Condition Assessment of Electrical Equipment with One Class Support Vector Machines Based on the Measurement of Partial Discharges

Guillermo Robles, Emilio Parrado-Hernández, Juan Manuel Martínez-Tarifa, 2018 .

Distributed support vector machines

Emilio Parrado-Hernández, Ángel Navia-Vázquez, D. Gutiérrez-González, 2006, IEEE Trans. Neural Networks.

Sequence Segmentation via Clustering of Subsequences

Emilio Parrado-Hernández, Fernando Díaz-de-María, Dario García-García, 2009, 2009 International Conference on Machine Learning and Applications.

Support vector machine interpretation

Emilio Parrado-Hernández, Ángel Navia-Vázquez, Á. Navia-Vázquez, 2006, Neurocomputing.

Multiple partial discharge source discrimination with multiclass support vector machines

Guillermo Robles, Emilio Parrado-Hernández, Juan Manuel Martínez-Tarifa, 2016, Expert Syst. Appl..