Enrique Romero

According to our database1, Enrique Romero authored at least 54 papers between 2004 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2020
On-The-Fly Syntheziser Programming with Fuzzy Rule Learning.
Entropy, 2020

Efficient Evaluation of the Partition Function of RBMs with Annealed Importance Sampling.
CoRR, 2020

On the use of pairwise distance learning for brain signal classification with limited observations.
Artif. Intell. Medicine, 2020

Interpreting response to TMZ therapy in murine GL261 glioblastoma by combining Radiomics, Convex-NMF and feature selection in MRI/MRSI data analysis.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019
Weighted contrastive divergence.
Neural Networks, 2019

Charting Perceptual Spaces with Fuzzy Rules.
Proceedings of the 2019 IEEE International Conference on Fuzzy Systems, 2019

2018
Modeling perceptual categories of parametric musical systems.
Pattern Recognit. Lett., 2018

Screening Dyslexia for English Using HCI Measures and Machine Learning.
Proceedings of the 2018 International Conference on Digital Health, 2018

Classifying and Generalizing Successful Parameter Combinations for Sound Design.
Proceedings of the Artificial Intelligence Research and Development, 2018

2017
Benchmarking the selection of the hidden-layer weights in extreme learning machines.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

DytectiveU: A Game to Train the Difficulties and the Strengths of Children with Dyslexia.
Proceedings of the 19th International ACM SIGACCESS Conference on Computers and Accessibility, 2017

2016
ECG assessment based on neural networks with pretraining.
Appl. Soft Comput., 2016

A methodological approach for algorithmic composition systems' parameter spaces aesthetic exploration.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016

A Rule-Extraction Algorithm for Describing Perceptual Parametric Subspaces in Algorithmic Composition Systems.
Proceedings of the Artificial Intelligence Research and Development, 2016

2015
A Fuzzy Inductive approach for rule-based modelling of high level structures in algorithmic composition systems.
Proceedings of the 2015 IEEE International Conference on Fuzzy Systems, 2015

2014
Automated classification of brain tumours from short echo time in vivo MRS data using Gaussian Decomposition and Bayesian Neural Networks.
Expert Syst. Appl., 2014

Stopping Criteria in Contrastive Divergence: Alternatives to the Reconstruction Error.
Proceedings of the 2nd International Conference on Learning Representations, 2014

Sepsis mortality prediction with the Quotient Basis Kernel.
Artif. Intell. Medicine, 2014

Assessment of Electrocardiograms with Pretraining and Shallow Networks.
Proceedings of the Computing in Cardiology, CinC 2014, 2014

Using the Fuzzy Inductive Reasoning methodology to improve coherence in algorithmic musical beat patterns.
Proceedings of the Artificial Intelligence Research and Development, 2014

2013
Identifying Useful Human Correction Feedback from an On-Line Machine Translation Service.
Proceedings of the IJCAI 2013, 2013

A quotient basis kernel for the prediction of mortality in severe sepsis patients.
Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

2012
Cohort-based kernel visualisation with scatter matrices.
Pattern Recognit., 2012

Comparing error minimized extreme learning machines and support vector sequential feed-forward neural networks.
Neural Networks, 2012

Data and knowledge visualization with virtual reality spaces, neural networks and rough sets: Application to cancer and geophysical prospecting data.
Expert Syst. Appl., 2012

Classification of human brain tumours from MRS data using Discrete Wavelet Transform and Bayesian Neural Networks.
Expert Syst. Appl., 2012

Towards interpretable classifiers with blind signal separation.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

2011
Using the Leader Algorithm with Support Vector Machines for Large Data Sets.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

Brain tumour classification using Gaussian decomposition and neural networks.
Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011

2010
Feature and model selection with discriminatory visualization for diagnostic classification of brain tumors.
Neurocomputing, 2010

Cohort-based kernel visualisation with scatter matrices.
Proceedings of the International Joint Conference on Neural Networks, 2010

2009
Neural Network-Based Visual Data Mining for Cancer Data.
Proceedings of the Encyclopedia of Artificial Intelligence (3 Volumes), 2009

Outlier exploration and diagnostic classification of a multi-centre <sup>1</sup>H-MRS brain tumour database.
Neurocomputing, 2009

An experimental study on methods for the selection of basis functions in regression.
Neurocomputing, 2009

Feature Selection with Single-Layer Perceptrons for a Multicentre 1H-MRS Brain Tumour Database.
Proceedings of the Bio-Inspired Systems: Computational and Ambient Intelligence, 2009

Frequency Selection for the Diagnostic Characterization of Human Brain Tumours.
Proceedings of the Artificial Intelligence Research and Development, 2009

2008
Performing Feature Selection With Multilayer Perceptrons.
IEEE Trans. Neural Networks, 2008

Exploratory Characterization of Outliers in a Multi-centre 1H-MRS Brain Tumour Dataset.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2008

Classification, Dimensionality Reduction, and Maximally Discriminatory Visualization of a Multicentre 1H-MRS Database of Brain Tumors.
Proceedings of the Seventh International Conference on Machine Learning and Applications, 2008

DSS-oriented exploration of a multi-centre magnetic resonance spectroscopy brain tumour dataset through visualization.
Proceedings of the ESANN 2008, 2008

2007
Comparing Support Vector Machines and Feedforward Neural Networks With Similar Hidden-Layer Weights.
IEEE Trans. Neural Networks, 2007

Heuristics for the selection of weights in sequential feed-forward neural networks: An experimental study.
Neurocomputing, 2007

Neural Network Based Virtual Reality Spaces for Visual Data Mining of Cancer Data: An Unsupervised Perspective.
Proceedings of the Computational and Ambient Intelligence, 2007

Data and Knowledge Visualization with Virtual Reality Spaces, Neural Networks and Rough Sets: Application to Geophysical Prospecting.
Proceedings of the International Joint Conference on Neural Networks, 2007

Search Strategies Guided by the Evidence for the Selection of Basis Functions in Regression.
Proceedings of the International Joint Conference on Neural Networks, 2007

Incremental and Decremental Learning for Linear Support Vector Machines.
Proceedings of the Artificial Neural Networks, 2007

Extended Linear Models with Gaussian Prior on the Parameters and Adaptive Expansion Vectors.
Proceedings of the Artificial Neural Networks, 2007

Selection of Basis Functions Guided by the L2 Soft Margin.
Proceedings of the Artificial Neural Networks, 2007

2006
A sequential algorithm for feed-forward neural networks with optimal coefficients and interacting frequencies.
Neurocomputing, 2006

Comparing Support Vector Machines and Feed-forward Neural Networks with Similar Parameters.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2006

On the selection of hidden neurons with heuristic search strategies for approximation.
Proceedings of the ESANN 2006, 2006

2005
Selection of Weights for Sequential Feed-Forward Neural Networks: An Experimental Study.
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

Feature Selection and Outliers Detection with Genetic Algorithms and Neural Networks.
Proceedings of the Artificial Intelligence Research and Development, 2005

2004
Margin maximization with feed-forward neural networks: a comparative study with SVM and AdaBoost.
Neurocomputing, 2004


  Loading...