Enrique Romero

发表

Cohort-based kernel visualisation with scatter matrices

Enrique Romero, Ana S. Fernandes, Tingting Mu, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

A Rule-Extraction Algorithm for Describing Perceptual Parametric Subspaces in Algorithmic Composition Systems

Enrique Romero, Àngela Nebot, Francisco Mugica, 2016, CCIA.

A quotient basis kernel for the prediction of mortality in severe sepsis patients

Enrique Romero, Alfredo Vellido, Vicent J. Ribas, 2013, ESANN.

Assessment of electrocardiograms with pretraining and shallow networks

Enrique Romero, Vicent J. Ribas, Anna Wojdel, 2014, Computing in Cardiology 2014.

A Fuzzy Inductive approach for rule-based modelling of high level structures in algorithmic composition systems

Enrique Romero, Àngela Nebot, Francisco Mugica, 2015, 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Selection of Basis Functions Guided by the L2 Soft Margin

Lluís A. Belanche Muñoz, Enrique Romero, Ignacio Barrio, 2007, ICANN.

Incremental and Decremental Learning for Linear Support Vector Machines

Lluís A. Belanche Muñoz, Enrique Romero, Ignacio Barrio, 2007, ICANN.

Search Strategies Guided by the Evidence for the Selection of Basis Functions in Regression

Lluís A. Belanche Muñoz, Enrique Romero, Ignacio Barrio, 2007, 2007 International Joint Conference on Neural Networks.

Cohort-based kernel visualisation with scatter matrices

Paulo J. G. Lisboa, Enrique Romero, Tingting Mu, 2012, Pattern Recognit..

Selection of Weights for Sequential Feed-Forward Neural Networks: An Experimental Study

Enrique Romero, 2005, IWANN.

Stopping Criteria in Contrastive Divergence: Alternatives to the Reconstruction Error

Enrique Romero, David Buchaca Prats, Jordi Delgado, 2014, ICLR.

On the selection of hidden neurons with heuristic search strategies for approximation

Lluís A. Belanche Muñoz, Enrique Romero, Ignacio Barrio, 2006, ESANN.

A sequential algorithm for feed-forward neural networks with optimal coefficients and interacting frequencies

Enrique Romero, René Alquézar, E. Romero, 2006, Neurocomputing.

Using the Leader Algorithm with Support Vector Machines for Large Data Sets

Enrique Romero, E. Romero, 2011, ICANN.

Modeling perceptual categories of parametric musical systems

Enrique Romero, Àngela Nebot, Francisco Mugica, 2018, Pattern Recognit. Lett..

Classifying and Generalizing Successful Parameter Combinations for Sound Design

Enrique Romero, Àngela Nebot, Francisco Mugica, 2018, CCIA.

Frequency Selection for the Diagnostic Characterization of Human Brain Tumours

Enrique Romero, Alfredo Vellido, Carlos Arizmendi, 2009, CCIA.

Using the Fuzzy Inductive Reasoning methodology to improve coherence in algorithmic musical beat patterns

Enrique Romero, Àngela Nebot, Francisco Mugica, 2014, CCIA.

Neural Network Based Virtual Reality Spaces for Visual Data Mining of Cancer Data: An Unsupervised Perspective

Enrique Romero, Julio J. Valdés, Alan J. Barton, 2007, IWANN.

Comparing Support Vector Machines and Feedforward Neural Networks With Similar Hidden-Layer Weights

Enrique Romero, Daniel Toppo, E. Romero, 2007, IEEE Transactions on Neural Networks.

Data and knowledge visualization with virtual reality spaces, neural networks and rough sets: application to geophysical prospecting

Enrique Romero, Julio J. Valdés, Ruben Gonzalez, 2020 .

Comparing error minimized extreme learning machines and support vector sequential feed-forward neural networks

Enrique Romero, René Alquézar, 2012, Neural Networks.

Automated classification of brain tumours from short echo time in vivo MRS data using Gaussian Decomposition and Bayesian Neural Networks

Enrique Romero, Alfredo Vellido, Daniel A. Sierra, 2014, Expert Syst. Appl..

Neural Network-Based Visual Data Mining for Cancer Data

Enrique Romero, Julio J. Valdés, Alan J. Barton, 2009, Encyclopedia of Artificial Intelligence.

Towards interpretable classifiers with blind signal separation

Paulo J. G. Lisboa, Enrique Romero, José David Martín-Guerrero, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Benchmarking the selection of the hidden-layer weights in extreme learning machines

Enrique Romero, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

DytectiveU: A Game to Train the Difficulties and the Strengths of Children with Dyslexia

Enrique Romero, Jeffrey P. Bigham, Luz Rello, 2017, ASSETS.

ECG assessment based on neural networks with pretraining

Enrique Romero, Vicent J. Ribas, Anna Wojdel, 2016, Appl. Soft Comput..

Feature Selection with Single-Layer Perceptrons for a Multicentre 1H-MRS Brain Tumour Database

Josep M. Sopena, Enrique Romero, Alfredo Vellido, 2009, IWANN.

An experimental study on methods for the selection of basis functions in regression

Lluís A. Belanche Muñoz, Enrique Romero, Ignacio Barrio, 2009, Neurocomputing.

Extended Linear Models with Gaussian Prior on the Parameters and Adaptive Expansion Vectors

Lluís A. Belanche Muñoz, Enrique Romero, Ignacio Barrio, 2007, ICANN.

Comparing Support Vector Machines and Feed-forward Neural Networks with Similar Parameters

Enrique Romero, Daniel Toppo, 2006, IDEAL.

Margin maximization with feed-forward neural networks: a comparative study with SVM and AdaBoost

Enrique Romero, Xavier Carreras, Lluís Màrquez i Villodre, 2004, Neurocomputing.

Heuristics for the selection of weights in sequential feed-forward neural networks: An experimental study

Enrique Romero, René Alquézar, E. Romero, 2007, Neurocomputing.

Performing Feature Selection With Multilayer Perceptrons

Josep M. Sopena, Enrique Romero, J. Sopena, 2008, IEEE Transactions on Neural Networks.

Brain tumour classification using Gaussian decomposition and neural networks

Enrique Romero, Alfredo Vellido, Daniel A. Sierra, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Screening Dyslexia for English Using HCI Measures and Machine Learning

Enrique Romero, Jeffrey P. Bigham, Luz Rello, 2018, DH.

Data and knowledge visualization with virtual reality spaces, neural networks and rough sets: Application to cancer and geophysical prospecting data

Enrique Romero, Julio J. Valdés, Alan J. Barton, 2012 .

Comparing Error Minimized Extreme Learning Machines and Support Vector Sequential Feedforward Neural Networks for Classification Problems

Enrique Romero, René Alquézar, 2010 .

Data mining of patients on weaning trials from mechanical ventilation using cluster analysis and neural networks

Enrique Romero, Pere Caminal, Beatriz F. Giraldo, 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

A Novel Semi-Supervised Methodology for Extracting Tumor Type-Specific MRS Sources in Human Brain Data

Paulo J. G. Lisboa, Enrique Romero, Margarida Julià-Sapé, 2013, PloS one.

Patients on Weaning Trials from Mechanical Ventilation Classified with Neural Networks and Feature Selection

Enrique Romero, Pere Caminal, René Alquézar, 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.