Publications sur l'Analyse de données fonctionnelles

• Articles
• Conférences internationales avec comité de lecture et publication des actes
• Conférences nationales avec comité de lecture et publication des actes

Articles

• (8) A data-driven functional projection approach for the selection of feature ranges in spectra with ICA or cluster analysis. Catherine Krier, Fabrice Rossi, Damien François et Michel Verleysen. Chemometrics and Intelligent Laboratory Systems, volume 91, numéro 1, pages 43-53. March 2008.
  [lien éditeur] [hal] [arXiv:0802.0287] [preprint (pdf)] [bib]
• (7) Un résultat de consistance pour des SVM fonctionnels par interpolation spline. Nathalie Villa et Fabrice Rossi. Comptes Rendus de l'Académie des Sciences - Série I, volume 343, numéro 8, pages 555-560. October 2006.
  [lien éditeur] [hal] [arXiv:0705.0210v1] [preprint (ps)] [preprint (pdf)] [bib]
• (6) Support Vector Machine For Functional Data Classification. Fabrice Rossi et Nathalie Villa. Neurocomputing, volume 69, numéro 7-9, pages 730-742. March 2006.
  [lien éditeur] [hal] [arXiv:0705.0209v1] [preprint (ps)] [preprint (pdf)] [bib]
  Cité par +/-

  1. B. Li and Q. Yu Classification of functional data: A segmentation approach. Computational Statistics & Data Analysis, 52(10):4790-4800, June 2008.
  2. C. Park, J.-Y. Koo, S. Kim, I. Sohn, and J. W. Lee. Classification of gene functions using support vector machine for time-course gene expression data. Computational Statistics & Data Analysis, 52(5):2578-2587, January 2008.
  3. Z.-J. Lee. An integrated algorithm for gene selection and classification applied to microarray data of ovarian cancer. Artificial Intelligence in Medicine, 42(1):81-93, January 2008.
  4. T. Laloë. A k-nearest neighbor approach for functional regression. Statistics & Probability Letters, 78(10):1189-1193, August 2008.
  5. Z.-J. Lee, S.-W. Lin, C.-C. V. Hsu, and Y.-P. Huang. Gene extraction and identification tumor/cancer for microarray data of ovarian cancer. In Proceedings of TENCON 2006 (IEEE Region 10 Conference), Hong-Kong, November 2006.
• (5) Theoretical Properties of Projection Based Multilayer Perceptrons with Functional Inputs. Fabrice Rossi et Brieuc Conan-Guez. Neural Processing Letters, volume 23, numéro 1, pages 55-70. February 2006.
  [lien éditeur] [hal] [arXiv:cs/0604001v1] [preprint (ps)] [preprint (pdf)] [bib]
• (4) Un modèle neuronal pour la régression et la discrimination sur données fonctionnelles. Fabrice Rossi et Brieuc Conan-Guez. Revue de Statistique Appliquée, volume LIII, numéro 4, pages 5-30. October 2005.
  [hal] [preprint (ps)] [preprint (pdf)] [bib]
• (3) Representation of Functional Data in Neural Networks. Fabrice Rossi, Nicolas Delannay, Brieuc Conan-Guez et Michel Verleysen. Neurocomputing, volume 64, pages 183-210. March 2005.
  [lien éditeur] [hal] [arXiv:0709.3641v1] [preprint (ps)] [preprint (pdf)] [bib]
  Cité par +/-

  1. F. Corona and A. Lendasse. Input selection and function approximation using the SOM: an application to spectrometric modeling. In Proceedings of the 5th Workshop on Self-Organizing Maps (WSOM 05), pages 653-660, Paris (France), September 2005.
  2. A. Vellido, P. J.G. Lisboa and D. Vicente, Robust analysis of MRS brain tumour data using t-GTM, Neurocomputing, 69(7-9):754-768, March 2006.
  3. M. Strickert, U. Seiffert, N. Sreenivasulu, W. Weschke, T. Villmann and B. Hammer, Generalized relevance LVQ (GRLVQ) with correlation measures for gene expression analysis, Neurocomputing, 69(7-9):651-659, March 2006.
  4. B.-J. Park, W. Pedrycz, and S.-K. Oh, Fuzzy polynomial neurons as neurofuzzy processing units, Neural Computing & Applications, 15(3-4):310-327, June 2006.
  5. K.-L. Du and M.N.S. Swamy. Neural Networks in a Softcomputing Framework. Springer, 2006.
  6. T. Villmann, E. Merényi, and U. Seiffert. Machine Learning Approaches and Pattern Recognition for Spectral Data, in Proceedings of XVIth European Symposium on Artificial Neural Networks (ESANN 2008), pages 433-444, Bruges (Belgium), April 2008.
• (2) Functional Multi-Layer Perceptron: a Nonlinear Tool for Functional Data Analysis. Fabrice Rossi et Brieuc Conan-Guez. Neural Networks, volume 18, numéro 1, pages 45-60. January 2005.
  [lien éditeur] [hal] [arXiv:0709.3642v1] [preprint (ps)] [preprint (pdf)] [bib]
  Cité par +/-

  1. Vellido, A. and Lisboa, P.J.G. Functional topographic mapping for robust handling of outliers in brain tumour data. In Proceedings of the European Symposium on Artificial Neural Networks (ESANN 2005), pages 133-138, Bruges (Belgium), April 2005.
  2. B.-J. Park, W. Pedrycz, and S.-K. Oh, Fuzzy polynomial neurons as neurofuzzy processing units, Neural Computing & Applications, 15(3-4):310-327, June 2006.
  3. L. Ferré and N. Villa. Multilayer perceptron with functional inputs: an inverse regression approach. Scandinavian Journal of Statistics, 33 (4), 807-823, December 2006.
  4. J.M. Poggi and C. Tuleau, Classification supervisée en grande dimension. Application à l'agrément de conduite automobile, Revue de Statistique Appliquée, LIV (4), 39-58, 2006
  5. K.-L. Du and M.N.S. Swamy. Neural Networks in a Softcomputing Framework. Springer, 2006.
  6. N. Hernández, R. J. Biscay, and I. Talavera. Support vector regression methods for functional data. In Progress in Pattern Recognition, Image Analysis and Applications, Proceedings of the 12th Iberoamerican Congress on Pattern Recognition, CIARP 2007, volume 4756 of Lecture Notes in Computer Science, Valparaiso (Chile), November 2007. Springer.
• (1) Estimation consistante des paramètres d'un modèle non linéaire pour des données fonctionnelles discrétisées aléatoirement. Fabrice Rossi et Brieuc Conan-Guez. Comptes Rendus de l'Académie des Sciences - Série I, volume 340, numéro 2, pages 167-170. January 2005.
  [lien éditeur] [hal] [preprint (ps)] [preprint (pdf)] [bib]

Conférences internationales avec comité de lecture et publication des actes

• (14) Constrained variable clustering for functional data representation. Fabrice Rossi et Yves Lechevallier. In Proceedings of the first joint meeting of the Société Francophone de Classification and the Classification and Data Analysis Group of the Italian Statistical Society (SFC-CLADAG 2008) (à paraître), Caserta, Italy. June 2008.
• (13) Recent advances in the use of SVM for functional data classification. Nathalie Villa et Fabrice Rossi. In Proceedings of 1rst International Workshop on Functional and Operatorial Statistics (IWFOS 2008) (à paraître), Toulouse, France. June 2008.
• (12) Consistency of Derivative Based Functional Classifiers on Sampled Data. Fabrice Rossi et Nathalie Villa. In Proceedings of XVIth European Symposium on Artificial Neural Networks (ESANN 2008), pages 445-450, Bruges, Belgium. April 2008.
  [ps] [pdf] [bib]
• (11) LS-SVM functional network for time series prediction. Tuomas Kärnä, Fabrice Rossi et Amaury Lendasse. In Proceedings of XIVth European Symposium on Artificial Neural Networks (ESANN 2006), pages 473-478, Bruges, Belgium. April 2006.
  [lien éditeur] [ps] [pdf] [bib]
• (10) Classification in Hilbert Spaces with Support Vector Machine. Fabrice Rossi et Nathalie Villa. In Proceedings of the XIth International Symposium on Applied Stochastic Models and Data Analysis (ASMDA 2005), pages 635-642, Brest, France. May 2005.
  [lien éditeur] [ps] [pdf] [bib]
  Cité par +/-

  1. M. Fromont and C. Tuleau, Functional classification with margin conditions, In Proceedings of 19th Annual Conference on Learning Theory (COLT 2006), Lecture Notes in Computer Science Volume 4005/2006, pages 94-108, Pittsburgh, PA, USA, June 22-25, 2006.
  2. C. Park, J.-Y. Koo, S. Kim, I. Sohn, and J. W. Lee. Classification of gene functions using support vector machine for time-course gene expression data. Computational Statistics & Data Analysis, 52(5):2578-2587, January 2008.
• (9) Support Vector Machine For Functional Data Classification. Nathalie Villa et Fabrice Rossi. In Proceedings of XIIIth European Symposium on Artificial Neural Networks (ESANN 2005), pages 467-472, Bruges, Belgium. April 2005.
  [lien éditeur] [ps] [pdf] [bib]
  Cité par +/-

  1. M. Strickert, U. Seiffert, N. Sreenivasulu, W. Weschke, T. Villmann and B. Hammer, Generalized relevance LVQ (GRLVQ) with correlation measures for gene expression analysis, Neurocomputing, 69(7-9):651-659, March 2006.
• (8) A Self Organizing Map for Dissimilarity Data. Aïcha El Golli, Brieuc Conan-Guez et Fabrice Rossi. In Proceedings of IFCS 2004, pages 61-68, Chicago, U.S.A.. July 2004.
  [ps] [pdf] [bib]
  Cité par +/-

  1. M. Martín-Merino and A. Muñoz, A Modification of the SOM Algorithm to Deal with Non-Symmetric Proximities, In Proceedings of the 5th Workshop on Self-Organizing Maps (WSOM 05), pages 569-578, Paris (France), September 2005.
  2. T. Ho-Phuoc and A. Guérin-Dugué. A new adaptation of self-organizing map for dissimilarity data. In A. Sandoval, F.and Prieto, J. Cabestany, and M. Graña, editors, Computational and Ambient Intelligence, Proceedings of 9th International Work-Conference on Artificial Neural Networks (IWANN 2007), volume 4507 of Lecture Notes in Computer Science, pages 219-226, San Sebastián (Spain), June 2007. Springer.
• (7) Phoneme Discrimination with Functional Multi-Layer Perceptron. Brieuc Conan-Guez et Fabrice Rossi. In Proceedings of IFCS 2004, pages 157-165, Chicago, U.S.A.. July 2004.
  [ps] [pdf] [bib]
• (6) Clustering Functional Data with the SOM algorithm. Fabrice Rossi, Brieuc Conan-Guez et Aïcha El Golli. In Proceedings of XIIth European Symposium on Artificial Neural Networks (ESANN 2004), pages 305-312, Bruges, Belgium. April 2004.
  [lien éditeur] [ps] [pdf] [bib]
  Cité par +/-

  1. J. A. Lee and M. Verleysen. Generalization of the lp norm for time series and its application to self-organizing maps. In Proceedings of the 5th Workshop on Self-Organizing Maps (WSOM 05), pages 733-740, Paris (France), September 2005.
  2. B. Hammer and T. Villmann. Classification using non standard metrics. In Proceedings of XIIIth European Symposium on Artificial Neural Networks (ESANN 2005), pages 303-316, Bruges (Belgium), April 2005.
  3. Vellido, A. and Lisboa, P.J.G. Functional topographic mapping for robust handling of outliers in brain tumour data. In Proceedings of the European Symposium on Artificial Neural Networks (ESANN 2005), pages 133-138, Bruges (Belgium), April 2005.
  4. M. Strickert, N. Sreenivasulu, W. Weschke, U. Seiffert, T. Villmann and B. Hammer, Generalized Relevance LVQ with Correlation Measures for Biological Data, Proceedings of the 13th European Symposium on Artificial Neural Networks (ESANN 2005), pages 331-338, Bruges (Belgium), April 2005.
  5. A. Vellido, P. J.G. Lisboa and D. Vicente, Robust analysis of MRS brain tumour data using t-GTM, Neurocomputing, 69(7-9):754-768, March 2006.
  6. M. Strickert, U. Seiffert, N. Sreenivasulu, W. Weschke, T. Villmann and B. Hammer, Generalized relevance LVQ (GRLVQ) with correlation measures for gene expression analysis, Neurocomputing, 69(7-9):651-659, March 2006.
  7. L. Ferré and N. Villa. Multilayer perceptron with functional inputs: an inverse regression approach. Scandinavian Journal of Statistics, 33 (4), 807-823, December 2006.
  8. S. Tokushige, H. Yadohisa, and K. Inada. Crisp and fuzzy k-means clustering algorithms for multivariate functional data, Computational Statistics, 22(1):1-16, April 2007.
  9. N. Shimizu and M. Mizuta. Functional clustering and functional principal points. In Proceedings of the 11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, volume 4693 of Lecture Notes in Computer Science, Vietri sul Mare (Italy), September 2007. Springer.
  10. S.-H. Huang, H.-R. Ke, and W.-P. Yang. Structure clustering for Chinese patent documents. Expert Systems with Applications, 34(4):2290-2297, May 2008.
• (5) Functional Radial Basis Function Network (FRBFN). Nicolas Delannay, Fabrice Rossi, Brieuc Conan-Guez et Michel Verleysen. In Proceedings of XIIth European Symposium on Artificial Neural Networks (ESANN 2004), pages 313-318, Bruges, Belgium. April 2004.
  [lien éditeur] [ps] [pdf] [bib]
  Cité par +/-

  1. Vellido, A. and Lisboa, P.J.G. Functional topographic mapping for robust handling of outliers in brain tumour data. In Proceedings of the European Symposium on Artificial Neural Networks (ESANN 2005), pages 133-138, Bruges (Belgium), April 2005.
• (4) Functional Preprocessing for Multilayer Perceptrons. Fabrice Rossi et Brieuc Conan-Guez. In Proceedings of XIIth European Symposium on Artificial Neural Networks (ESANN 2004), pages 319-324, Bruges, Belgium. April 2004.
  [lien éditeur] [ps] [pdf] [bib]
• (3) Multi-Layer Perceptrons for Functional Data Analysis: a Projection Based Approach. Brieuc Conan-Guez et Fabrice Rossi. In José R. Dorronsoro, editors, Artificial Neural Networks (ICANN 2002), pages 667-672, Madrid, Spain. August 2002.
  [lien éditeur] [ps] [pdf] [bib]
• (2) Functional Data Analysis With Multi Layer Perceptrons. Fabrice Rossi, Brieuc Conan-Guez et François Fleuret. In Proceedings of IJCNN (part of WCCI), volume 3, pages 2843-2848, Honolulu, USA. May 2002.
  [lien éditeur] [ps] [pdf] [bib]
• (1) Theoretical Properties of Functional Multi Layer Perceptrons. Fabrice Rossi, Brieuc Conan-Guez et François Fleuret. In Proceedings of Xth European Symposium on Artificial Neural Networks (ESANN 2002), pages 7-12, Bruges, Belgium. April 2002.
  [lien éditeur] [ps] [pdf] [bib]
  Cité par +/-

  1. B. Hammer and B. J. Jain. Neural methods for non-standard data. In Proceedings of XIIth European Symposium on Artificial Neural Networks (ESANN 2004), pages 281-292, Bruges (Belgium), April 2004.
  2. B. Hammer and T. Villmann. Mathematical aspects of neural networks. In Proceedings of XIth European Symposium on Artificial Neural Networks (ESANN 2003), pages 59-72, Bruges (Belgium), April 2003.

Conférences nationales avec comité de lecture et publication des actes

• (4) SVM fonctionnels par interpolation spline. Nathalie Villa et Fabrice Rossi. In Actes des 38ièmes Journées de Statistique de la SFDS, Clamart, France. May/June 2006.
  [ps] [pdf] [bib]
• (3) Estimation consistante d'un modèle paramétrique fonctionnel en présence de discrétisation aléatoire. Fabrice Rossi et Brieuc Conan-Guez. In Actes des XXXVèmes journées de Statistique de la SFdS, pages 819-822, Lyon, France. Juin 2003.
  [ps] [pdf] [bib]
• (2) Modélisation supervisée de données fonctionnelles par perceptron multi-couches. Fabrice Rossi et Brieuc Conan-Guez. In Actes des Neuvièmes journées de la Société Francophone de Classification (conférence invitée), pages 93-100, Toulouse, France. Septembre 2002.
  [ps] [pdf] [bib]
• (1) Approche Régularisée du Traitement de Données Fonctionnelles par un Perceptron Multi-Couches. Brieuc Conan-Guez et Fabrice Rossi. In Actes des Neuvièmes journées de la Société Francophone de Classification, pages 169-172, Toulouse, France. Septembre 2002.
  [ps] [pdf] [bib]
  Cité par +/-

  1. L. Ferré and A.-F. Yao, Smoothed functional inverse regression, Statistica Sinica 15(2005), 665-683.

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