Página personal de José Mª Valls

Información de contacto (contact information)



Docencia (teaching)

Investigación (research)

Publicaciones (publications)

Proyectos de investigación (research projects)

 

 



 

Docencia (teaching)


Ingeniería en Informática

 Grado en Ingeniería Informática

 Máster en Ciencia y Tecnología Informática

 Ingeniería Técnica en Informática de Gestión

 

Publicaciones docentes

  • David Camacho Fernández, José María Valls Ferrán, Jesús García Herrero, José Manuel Molina, Enrique Bueno.
    Programación,  algoritmos y Ejercicios Resueltos en Java.
    ISBN: 84-205-4024-2   
    Editorial:  Pearson / Prentice-Hall (2003)
  • José María Valls Ferrán, David Camacho Fernández
    Programación Estructurada y algoritmos en Pascal.
    ISBN: 84-205-4246-6
    Editorial: Pearson / Prentice-Hall (2004)
     

 

Investigación (research)


Grupos de Investigación (research groups)

Líneas de investigación  (research interest)

  • Redes de Neuronas (Neural Networks)
  • Computación Evolutiva (Evolutionary Computation)
  • Aprendizaje Automático (Machine Learning)

Publicaciones

Journals

  • Cristóbal Luque, José M. Valls, Pedro Isasi. Time Series Prediction Evolving Voronoi Regions
    Applied Intelligence. To appear (2009)
  • Ricardo Aler, Jose M. Valls, David Camacho and Alberto Lopez. Programming Robosoccer Agents by Modeling Human Behavior.
    Expert Systems With Applications. Vol 36, pp 1850-1859. (2009)
  • José M. Valls, Inés M. Galván and Pedro Isasi. Learning Radial Basis Neural Networks in a lazy way: a comparative study.
    Neurocomputing. Vol 71, pp 2529 -2537. (2008)
  • César Estébanez, José M. Valls and Ricardo Aler. GPPE: A Novel Method to Generate Ad-hoc Feature Extractors for Prediction in Financial Domains.
    Applied Intelligence. Vol  29: pp: 174-185. (2008)
  • José M. Valls, Inés M. Galván, Pedro Isasi. LRBNN: A Lazy RBNN Model.
    AI Communications. Vol 20 (2). pp 71-86 (2007)
  • José M. Valls,  Ricardo Aler, Oscar Fernández. Evolving Generalized Euclidean Distances for Training RBNN
    Computing and Informatics. Vol 26, pp 33-43 (2007).
  • José M. Valls, Inés M. Galván, Pedro Isasi. Improving the generalization ability of RBNN using a selective strategy  based on the gaussian kernel function
    Computing and Informatics. Vol 25, pp 1-15 (2006).
  • José M. Valls, Inés M. Galván, Pedro Isasi. Lazy learning in Radial Basis Neural Networks: a way of achieving more accurate models
    Neural Processing Letters. Vol 20(2), pp 105 - 124 (2004).
  • José M. Molina, Inés M. Galván, José M. Valls, Andrés Leal.Optimizing the number of learning cycles in the design of radial basis neural networks using a multi-agent System.
    Computing and Informatics. Vol 20, pp 429 - 449    (2001).
  • Inés M. Galván, Pedro Isasi, Ricardo Aler, José M. Valls. A Selective Learning Method to Improve the Generalization of Multilayer Feedforward Neural Networks.
    International Journal of Neural Systems. Vol 11, pp 167 - 177 (2001)
     

 International Conferences

  • José M. Valls, Ricardo Aler. Optimizing Linear and Quadratic Data Transformations for Classification Tasks.
    9th International Conference on Intelligent Systems Design and Applications (ISDA 2009).Pisa (Italia). To appear.
  • José M Valls, and Ricardo Aler. Optimizing Data Transformations for Classification Tasks
    International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2009). Burgos, Sept 2009.
    Lecture Notes in Computer Science 5788.
  • C. Luque, D. Quintana, J. M Valls, and P. Isasi. Two-Layered Evolutionary Forecasting for IPO Underpricing.
    IEEE Congress on Evolutionary Computation (CEC 2009). Special Sesion on Finance and Economics. pp 2374--2378. Trondheim (Norway), May 2009.
  • César Estébanez,  Ricardo Aler,  José M. Valls,  Pablo Alonso. An experimental study on fitness distributions of tree shapes in GP with One-Point Crossover.
    12th European Conference on Genetic Programming (EuroGP 2009). Tübingen (Germany), April 2009. Lecture Notes in Computer Science.
  • Inés M. Galván, José M. Valls, Nicolas Lecomte and Pedro Isasi. A lazy Approach for Machine Learning Algorithms.
    5th IFIP Conference on Artificial Intelligence Applications & Innovations (AIAI 2009). Thesalonica (Grecia), April 2009
  • R. Aler, I. Galván, J. M. Valls. Improving Classification for Brain Computer Interfaces using Transitions and a Moving Window.
    International Conference on Bio-inspired Systems and Signal Processing. Biostec 2009. BIOSIGNALS. Porto (Portugal), Jan 2009.
  • R. Aler, C. Estébanez and J. Valls. Hybridization of Clustering and Local Search for the Frequency Assignment Problem
    International Conference on Metaheuristics and Nature Inspired Computing (Meta'08).  Hammamet (Túnez), Oct 2008.
  • F.Luna, C. Estébanez, C. León, J.M. Chaves-González, E. Alba, R. Aler, C. Segura, M.A. Vega-Rodríguez, A.J. Nebro, J.M. Valls, G. Miranda, J.A. Gómez-Pulido.
    Metaheuristics for Solving a Real-World Frequency Assignment Problem in GSM Networks.
    Genetic and Evolutionary Computation Conference (GECCO 2008), pp 1579--1586. Atlanta (USA), July 2008.
  • Cristóbal Luque, José M. Valls, Pedro Isasi. Time Series Forecasting by means of Evolutionary Algorithms.
    Parallel and Distributed Processing Symposium. IPDPS 2007. IEEE International. pp 1-7. California (USA), March 2007.
  • José M. Valls, Inés M. Galván, Pedro Isasi. Lazy training of Radial Basis Neural Networks.
    International Conference on Artificial Neural Networks (ICANN 2006). Artificial Neural Networks, Lecture Notes in Computer Science, Vol 4131/2006, pp 198-207. Athens (Greece), Sep 2006.
  • I. Galván, Y. Sáez, J. M. Valls P. Isasi. Improving the Prediction of Electoral Results by Selecting Representative Polling Stations.
    Applied Mathematical Programming and Modelling (Apmod 2006)
  • César Estébanez, José M. Valls and Ricardo Aler. Projecting Financial Data using Genetic Programming in Classification and Regression Tasks.
    9th European Conference on Genetic Programming: EuroGP 2006. Lecture Notes in Computer Science, vol LNCS  3905 / 2006,  pp  202 - 212. Budapest (Hungría), April 2006.
  • César Estébanez, Ricardo Aler, José M. Valls. Genetic Programming Based Data Projections for Classification Tasks.
    International Conference on Computational Intelligence, ICCI 2005. pp 56-61. Prague, Czech Republic. August 2005.
  • Ricardo Aler, Oscar García, Jose M. Valls. Correcting and Improving Imitation Models of Humans for Robosoccer Agents.
    IEEE Congress on Evolutionary Computation (CEC'05), Special Session on Games.  pp 2402-2409. Edinburgh (UK). Sep 2005.
  • César Estébanez, José M. Valls,  Ricardo Aler and Inés M. Galván. A First Attempt at Constructing Genetic Programming Expressions for EEG Classification
    15th International Conference on Artificial Neural Networks (ICANN 2005). Lecture Notes in Computer Science, vol LNCS 3696, pp  665--670. Varsovia (Polonia), Sept 2005.
  • José M. Valls, Ricardo Aler and Oscar Fernández.Using a Mahalanobis-like  distance to train Radial Basis Neural Networks.
    8th International Work-Conference on Artificial Neural Networks (IWANN 2005), Lecture Notes in Computer Science, vol 3512, pp 257-263. Vilanova i la Geltrú (Barcelona), June 2005.
  • Pedro Isasi, José M. Valls,  Inés M. Galván. A better selection of patterns in lazy learning radial basis neural networks.
    7th. International Work Conference on Artificial and Natural Neural Networks (IWANN 2003), Lecture Notes in Computer Science, vol 2686 , pp 278-285. Menorca, June 2003.
  • José M. Valls,  Inés M. Galván,  Pedro Isasi. How the selection of training patterns can improve the generalization capability in Radial Basis Neural Networks.
    IASTED International Conference on Artificial Intelligence and Applications. Innsbruck (Austria), Feb 2003.
  • José M. Valls, Andrés Leal, Inés M. Galván, José M. Molina. Designing Radial Basis Neural Networks using a Distributed Arquitecture.
    International Conference on Neural Networks and Applications (NNA '01). Advances in Neural Networks and Applications. Artificial Intelligence Series, pp 177--182. Tenerife (Spain), Feb 2001.
  • Inés M. Galván, Pedro Isasi, José M. Valls. Automatic selection of training patterns to improve the generalization of Multilayer Feedforward Neural Networks.
    International Conference on Neural Networks and Applications (NNA '01). Advances in Neural Networks and Applications. Artificial Intelligence Series, pp 177--182. Tenerife (Spain), Feb 2001.
  • José M. Valls, Pedro Isasi, Inés M. Galván. Deferring the Learning for Better Generalization in Radial Basis Neural Networks.
    International Conference on Artificial Neural Networks (ICANN 2001). Artificial Neural Networks, Lecture Notes in Computer Science, vol 2130, pp 189-195. Viena (Austria), Aug 2001.
  • José M. Valls, Inés M. Galván, Pedro Isasi. Specific Training of Radial Basis Neural Networks for Function Approximation.
    The 4th World Multiconference on Systemics, Cybernetics and Informatics SCI 2000. pp 468--472. Orlando (USA)
  • José M. Valls, Inés M. Galván, José Manuel Molina. Multiagent System for designing optimal Radial Basis Neural Networks.
    8th Information Processing and Management of Uncertainty in Knowledge-Based Systems Conference (IPMU 2000). pp: 1539--1545. Madrid (Spain), Jul 2000.
     

 

Proyectos de investigación

 

  • Técnicas de aprendizaje automático aplicadas al interfaz cerebro-ordenador (2008)
  • Computación evolutiva para tareas de clasificación en minería de datos (2007)
  • Técnicas de Computación con Inspiración Biológica para la minería de datos (2006)