Machine Learning Group

 
 

Our research interests include: 

  1. •Algorithms able to learn from classification or regression tasks, 

  2. •Machine learning applications to livestock, food productions, sensory analysis, bioinformatics


People

  1. Staff

  2. Juan José del Coz

  3. Oscar Luaces

  4. Jaime Alonso

  5. Jorge Díez

  6. José Ramón Quevedo

  7. Elena Montañés Roces

  8. Antonio Bahamonde


  10. PhD Students

  11. José Barranquero Tolosa

 

Welcome to the home page of the

Machine Learning Group of the

Artificial Intelligence Center.


University of Oviedo at Gijón.

Recent publications (draft versions)


  1. •Jaime Alonso, Ángel Rodríguez Castañón, Antonio Bahamonde: Support Vector Regression to predict carcass weight in beef cattle in advance of the slaughter. Computers and Electronics in Agriculture 91 (2013) 116–120. (pdf)

  2. •J. J. del Coz, J. Díez, A. Bahamonde, F. Goyache: Learning data structure from classes: a case study applied to population genetics. Information Sciences. Vol. 193 (2012), 22-35. (pdf)

  3. •Elena Montañés, José Ramón Quevedo, Juan José del Coz: Aggregating Independent and Dependent Models to Learn Multi-label Classifiers. European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD‘2011). (pdf)

  4. •Gerardo Lastra, Oscar Luaces, Jose Ramon Quevedo, Antonio Bahamonde: Graphical Feature Selection for Multilabel Classification Tasks. Proceedings of Intelligent Data Analysis, IDA 2011. (pdf)

  5. •Jose R Quevedo, Oscar Luaces, Antonio Bahamonde: Multilabel classifiers with a probabilistic thresholding strategy. Pattern Recognition, Volume 45 (2), February 2012, Pages 876-883. (pdf) (software)

  6. •Jose R Quevedo, Antonio Bahamonde, Miguel Perez-Enciso, Oscar Luaces: Disease Liability Prediction from Large Scale Genotyping Data Using Classifiers with a Reject Option. IEEE/ACM transactions on computational biology and bioinformatics. 03/2011 (pdf)

  7. •Quevedo, J.R.; Montañés, E.; Luaces, O.; del Coz, J.J.: Adapting Decision DAGs for Multipartite Ranking. European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD’2010). Proceedings, Part III. Lecture Notes in Computer Science Springer 2010. Vol. 6323, pp. 115-130. (pdf) (poster)

  8. •Luaces, O.; Quevedo, J.R.; Enciso, M.; Díez, J.; del Coz, J.J.; Bahamonde, A.: Explaining the Genetic Basis of Complex Quantitative Traits through Prediction Models. Journal of Computational Biology. 2010 Dec; 17(12):1711- 1723. (pdf)

  9. •Díez, J.; Del Coz, J.J.; Bahamonde, A.: A semi-dependent decomposition approach to learn hierarchical classifiers. Pattern Recognition, Volume 43, Issue 11, November 2010, Pages 3795-3804 (pdf)

  10. •Del Coz, J.J.; Díez, J.; Bahamonde, A.: Learning nondeterministic classifiers. Journal of Machine Learning Research 10(Oct) :2273-2293, 2009.

  11. •Díez, J.; Del Coz, J.J.; Luaces, O.; Bahamonde, A.: Soft Margin Tress. ECML-PKDD 2009.   In W. Buntine et al. editors , Machine Learning and Knowledge Discovery in Databases, Part I, LNAI 5781,pp 302-314. Springer, 2009. (pdf)

  12. •Luaces, O.; Taboada, F; Albaiceta, G. M.; Domínguez, L. A., Enríquez, P.; GRECIA Group; Bahamonde, A.: Predicting the probability of survival in intensive care unit patients from a small number of variables and training examples. Artificial Intelligence in Medicine, Volume 45, Issue 1, 2009, pp. 63-76. (doi) (pdf)

  13. •Alonso, J.; del Coz, J. J.; Díez, J.; Luaces, O.; Bahamonde, A.: Learning to predict one or more ranks in ordinal regression tasks. In W. Daelemans, B. Goethals, K. Morik, editors, Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2008), LNAI 5211, pages 39-54, 2008. Springer-Verlag 2008. (pdf)

  14. •Díez, J.; Del Coz, J. J.; Luaces, O.; Bahamonde, A.: Clustering people according to their preference criteria. Expert Systems with Applications, 34 (2), 2008, pp. 1274-1284. (doi)

  15. •Pérez-Enciso, M.; Quevedo, J. R.; Bahamonde, A.: Genetical genomics: use all data. BMC Genomics 2007, 8:69.


  16. •Quevedo, J. R.; Bahamonde, A.; Luaces, O.: A simple and efficient methods for variable ranking according to their usefulness for learning. Computational Statistics and Data Analysis, Vol. 52, Issue 1, 2007, pp. 578-595. Draft version (pdf) (doi).

  17. •Bahamonde, A.; Díez, J.; Quevedo, J. R.; Luaces, O.; Del Coz, J. J. (2007): How to learn consumer preferences from the analysis of sensory data by means of support vector machines (SVM).  Trends in Food Science & Technology, 18 (1), 2007, pp. 20-28. (pdf)

  18. • Luaces, O.; Quevedo, J.R.; Taboada, F.; Albaiceta, G.M.; Bahamonde, A. (2007): Prediction of probability of survival in critically ill patients optimizing the Area Under the ROC Curve. Proceedings of the 20th. International Joint Conference on Artificial Intelligence (IJCAI'07), Hyderabad, India, 2007, pp. 956-961. (pdf)  (pdf-IJCAI07) 


 

Full list publications (draft versions)

  1. Most of our publications can be downloaded following this link.