José María Valls

A. Echeverría, José María Valls, Ricardo Aler: Evolving linear transformations with a rotation-angles/scaling representation. Expert Syst. Appl. 39(3): 3276-3282 (2012)

Ricardo Aler, Inés María Galván, José María Valls: Applying evolution strategies to preprocessing EEG signals for brain-computer interfaces. Inf. Sci. 215: 53-66 (2012)

Cristóbal Luque, José María Valls, Pedro Isasi: Time series prediction evolving Voronoi regions. Appl. Intell. 34(1): 116-126 (2011)

Francisco Luna, César Estébanez, Coromoto León, José M. Chaves-González, Antonio J. Nebro, Ricardo Aler, Carlos Segura, Miguel A. Vega-Rodríguez, Enrique Alba, José María Valls, Gara Miranda, Juan Antonio Gómez Pulido: Optimization algorithms for large-scale real-world instances of the frequency assignment problem. Soft Comput. 15(5): 975-990 (2011)

Ricardo Aler, Inés María Galván, José María Valls: Evolving spatial and frequency selection filters for Brain-Computer Interfaces. IEEE Congress on Evolutionary Computation 2010: 1-7

Ricardo Aler, José María Valls, David Camacho, Alberto López: Programming Robosoccer agents by modeling human behavior. Expert Syst. Appl. 36(2): 1850-1859 (2009)

Ricardo Aler, José María Valls, David Camacho, Alberto López: Corrigendum "Programming Robosoccer agents by modeling human behavior" [Experts Systems with Applications 36 (2P1) (2009) 1850-1859]. Expert Syst. Appl. 36(9): 11992 (2009)

Ricardo Aler, Inés María Galván, José María Valls: Improving Classification for Brain Computer Interfaces using Transitions and a Moving Window. BIOSIGNALS 2009: 65-71

Cristóbal Luque, David Quintana, José María Valls, Pedro Isasi: Two-layered evolutionary forecasting for IPO underpricing. IEEE Congress on Evolutionary Computation 2009: 2374-2378

César Estébanez, Ricardo Aler, José María Valls, Pablo Alonso: An Experimental Study on Fitness Distributions of Tree Shapes in GP with One-Point Crossover. EuroGP 2009: 244-255

José María Valls, Ricardo Aler: Optimizing Data Transformations for Classification Tasks. IDEAL 2009: 176-183

Inés María Galván, José María Valls, Nicolas Lecomte, Pedro Isasi: A Lazy Approach for Machine Learning Algorithms. AIAI 2009: 517-522

José María Valls, Ricardo Aler: Optimizing Linear and Quadratic Data Transformations for Classification Tasks. ISDA 2009: 1025-1030

César Estébanez, José María Valls, Ricardo Aler: GPPE: a method to generate ad-hoc feature extractors for prediction in financial domains. Appl. Intell. 29(2): 174-185 (2008)

Francisco Luna, César Estébanez, Coromoto León, José M. Chaves-González, Enrique Alba, Ricardo Aler, Carlos Segura, Miguel A. Vega-Rodríguez, Antonio J. Nebro, José María Valls, Gara Miranda, Juan Antonio Gómez Pulido: Metaheuristics for solving a real-world frequency assignment problem in GSM networks. GECCO 2008: 1579-1586

José María Valls, Inés María Galván, Pedro Isasi: LRBNN: A Lazy Radial Basis Neural Network model. AI Commun. 20(2): 71-86 (2007)

José María Valls, Ricardo Aler, Oscar Fernández: Evolving Generalized Euclidean Distances for Training RBNN. Computers and Artificial Intelligence 26(1): 33-43 (2007)

César Estébanez, Ricardo Aler, José María Valls: A Method Based on Genetic Programming for Improving the Quality of Datasets in Classification Problems. IJCSA 4(1): 69-80 (2007)

Cristóbal Luque del Arco-Calderón, José María Valls, Pedro Isasi Viñuela: Time Series Forecasting by means of Evolutionary Algorithms. IPDPS 2007: 1-7

José María Valls, Inés María Galván, Pedro Isasi Viñuela: Improving the Generalization Ability of RBNN Using a Selective Strategy Based on the Gaussian Kernel Function. Computers and Artificial Intelligence 25(1): 1-15 (2006)

César Estébanez, José María Valls, Ricardo Aler: Projecting Financial Data Using Genetic Programming in Classification and Regression Tasks. EuroGP 2006: 202-212

José María Valls, Inés María Galván, Pedro Isasi: Lazy Training of Radial Basis Neural Networks. ICANN (1) 2006: 198-207

Ricardo Aler, Oscar Garcia, José María Valls: Correcting and improving imitation models of humans for Robosoccer agents. Congress on Evolutionary Computation 2005: 2402-2409

César Estébanez, José María Valls, Ricardo Aler, Inés María Galván: A First Attempt at Constructing Genetic Programming Expressions for EEG Classification. ICANN (1) 2005: 665-670

José María Valls, Ricardo Aler, Oscar Fernández: Using a Mahalanobis-Like Distance to Train Radial Basis Neural Networks. IWANN 2005: 257-263

César Estébanez, Ricardo Aler, José María Valls: Genetic Programming Based Data Projections for Classification Tasks. IEC (Prague) 2005: 56-61

José María Valls, Inés María Galván, Pedro Isasi: Lazy Learning in Radial Basis Neural Networks: A Way of Achieving More Accurate Models. Neural Processing Letters 20(2): 105-124 (2004)

José María Valls, Inés María Galván, Pedro Isasi: How the Selection of Training Patterns can Improve the Generalization Capability in Radial Basis Neural Networks. Applied Informatics 2003: 275-280

Pedro Isasi, José María Valls, Inés María Galván: A Better Selection of Patterns in Lazy Learning Radial Basis Neural Networks. IWANN (1) 2003: 278-285

José M. Molina, Inés María Galván, José María Valls, Andrés Leal: Optimizing the Number of Learning Cycles in the Design of Radial Basis Neural Networks Using a Multi-Agent System. Computers and Artificial Intelligence 20(5) (2001)

Inés María Galván, Pedro Isasi, Ricardo Aler, José María Valls: A Selective Learning Method to Improve the Generalization of Multilayer Feedforward Neural Networks. Int. J. Neural Syst. 11(2): 167-177 (2001)

José María Valls, Pedro Isasi, Inés María Galván: Deferring the Learning for Better Generalization in Radial Basis Neural Networks. ICANN 2001: 189-195

José María Valls, José M. Molina, Inés María Galván: Sistema Multiagente para el diseño de Redes de Neuronas de Base Radial Óptimas. Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial 4(10): 18-25 (2000)