Publications

Vous trouverez ici une liste complète de mes publications. Si vous avez besoin d'une version électronique (postscript ou pdf) d'un article indiqué ici, vous pouvez me la demander par email. Cette liste mélange des publications scientifiques, des rapports techniques et des articles de vulgarisation.

• Articles
• Editoriaux
• Articles de vulgarisation
• Ouvrage collectif
• Chapitres d'ouvrage collectif
• Conférences internationales avec comité de lecture et publication des actes
• Conférences nationales avec comité de lecture et publication des actes
• Rapports

Articles

• (20) Représentation d'un grand réseau à partir d'une classification hiérarchique de ses sommets. Fabrice Rossi et Nathalie Villa-Vialaneix. Journal de la Société Française de Statistique, volume 152, numéro 3, pages 34-65. 2011.
  [lien éditeur] [hal] [preprint (pdf)] [bib] [Scholar search]
• (19) Consistency of Functional Learning Methods Based on Derivatives. Fabrice Rossi et Nathalie Villa-Vialaneix. Pattern Recognition Letters, volume 32, numéro 8, pages 1197-1209. June 2011.
  [lien éditeur] [arXiv:1105.0204] [hal] [preprint (pdf)] [bib] [Scholar search]
• (18) Optimizing an Organized Modularity Measure for Topographic Graph Clustering: a Deterministic Annealing Approach. Fabrice Rossi et Nathalie Villa-Vialaneix. Neurocomputing, volume 73, numéro 7-9, pages 1142-1163. March 2010.
  [lien éditeur] [arXiv:1009.1318] [hal] [preprint (pdf)] [bib] [Scholar search]
• (17) Exploratory Analysis of Functional Data via Clustering and Optimal Segmentation. Georges Hébrail, Bernard Hugueney, Yves Lechevallier et Fabrice Rossi. Neurocomputing, volume 73, numéro 7-9, pages 1125-1141. March 2010.
  [lien éditeur] [dataset] [arXiv:1004.0456] [hal] [preprint (pdf)] [bib] [Scholar search]
• (16) Accélération des cartes auto-organisatrices sur tableau de dissimilarités par séparation et évaluation. Brieuc Conan-Guez et Fabrice Rossi. Revue des Nouvelles Technologies de l'Information, volume RNTI-C-2, pages 1-16. June 2008.
  [lien éditeur] [hal] [arXiv:0802.0252] [preprint (ps)] [preprint (pdf)] [bib] [Scholar search]
• (15) Batch kernel SOM and related Laplacian methods for social network analysis. Romain Boulet, Bertrand Jouve, Fabrice Rossi et Nathalie Villa-Vialaneix. Neurocomputing, volume 71, numéro 7-9, pages 1257-1273. March 2008.
  [Nature news] [Le Figaro] [lien éditeur] [hal] [arXiv:0801.0848] [preprint (ps)] [preprint (pdf)] [bib] [Scholar search]
• (14) 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] [Scholar search]
• (13) Fast Selection of Spectral Variables with B-Spline Compression. Fabrice Rossi, Damien François, Vincent Wertz, Marc Meurens et Michel Verleysen. Chemometrics and Intelligent Laboratory Systems, volume 86, numéro 2, pages 208-218. April 2007.
  [lien éditeur] [hal] [arXiv:0709.3639v1] [preprint (ps)] [preprint (pdf)] [bib] [Scholar search]
  Cité par +/-

  1. L. Komsta, R. Skibiński, M. Paryło and K. Dudek. The Basis Function Regression in pharmaceutical analysis Theory and example of application. Journal of Pharmaceutical and Biomedical Analysis 47(4-5):659-669, August 2008.
  2. W. Saeys, B. De Ketelaere, and P. Darius. Potential applications of functional data analysis in chemometrics. Journal of Chemometrics, 22(5):335 -- 344, May 2008.
• (12) Resampling methods for parameter-free and robust feature selection with mutual information. Damien François, Fabrice Rossi, Vincent Wertz et Michel Verleysen. Neurocomputing, volume 70, numéro 7-9, pages 1276-1288. March 2007.
  [lien éditeur] [hal] [arXiv:0709.3640v1] [preprint (ps)] [preprint (pdf)] [bib] [Scholar search]
  Cité par +/-

  1. C.-H. Chueh and J.-T. Chien. Reliable feature selection for language model adaptation. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008), pages 5089-5092, April 2008.
  2. Y. Miche, P. Bas, C. Jutten, O. Simula, and A. Lendasse. A methodology for Building Regression Models using Extreme Learning Machine: OP-ELM, in Proceedings of XVIth European Symposium on Artificial Neural Networks (ESANN 2008), pages 247-252, Bruges (Belgium), April 2008.
• (11) Un résultat de consistance pour des SVM fonctionnels par interpolation spline. Nathalie Villa-Vialaneix 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] [Scholar search]
• (10) Une adaptation des cartes auto-organisatrices pour des données décrites par un tableau de dissimilarités. Aïcha El Golli, Fabrice Rossi, Brieuc Conan-Guez et Yves Lechevallier. Revue de Statistique Appliquée, volume LIV, numéro 3, pages 33-64. October 2006.
  [hal] [arXiv:0709.3586v1] [preprint (ps)] [preprint (pdf)] [bib] [Scholar search]
  Cité par +/-

  1. N. Villa and R. Boulet, Clustering a medieval social network by SOM using a kernel based distance measure, in Proceedings of XVth European Symposium on Artificial Neural Networks (ESANN 2007), pages 31-36, Bruges (Belgium), April 2007.
  2. N. Delestre and N. Malandain. Analyse et représentation en deux dimensions de traces pour le suivi de l'apprenant, Revue STICEF, Volume 14, 2007, ISSN : 1764-7223.
• (9) Fast Algorithm and Implementation of Dissimilarity Self-Organizing Maps. Brieuc Conan-Guez, Fabrice Rossi et Aïcha El Golli. Neural Networks, volume 19, numéro 6-7, pages 855-863. July-August 2006.
  [lien éditeur] [hal] [arXiv:0709.3461v1] [preprint (ps)] [preprint (pdf)] [bib] [Scholar search]
  Cité par +/-

  1. C. Hung. A constrained neural learning rule for eliminating the border effect in online self-organising maps. Connection Science, 20(1):1-20, March 2008.
  2. N. Villa and R. Boulet, Clustering a medieval social network by SOM using a kernel based distance measure, in Proceedings of XVth European Symposium on Artificial Neural Networks (ESANN 2007), pages 31-36, Bruges (Belgium), April 2007.
  3. 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.
• (8) Support Vector Machine For Functional Data Classification. Fabrice Rossi et Nathalie Villa-Vialaneix. Neurocomputing, volume 69, numéro 7-9, pages 730-742. March 2006.
  [lien éditeur] [hal] [arXiv:0705.0209v1] [preprint (ps)] [preprint (pdf)] [bib] [Scholar search]
  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.
  6. A. Berlinet, G. Biau, and L. Rouvière. Functional supervised classification with wavelets. Annales de l'ISUP, 52:61--80, 2008.
• (7) Mutual information for the selection of relevant variables in spectrometric nonlinear modelling. Fabrice Rossi, Amaury Lendasse, Damien François, Vincent Wertz et Michel Verleysen. Chemometrics and Intelligent Laboratory Systems, volume 80, numéro 2, pages 215-226. February 2006.
  [lien éditeur] [hal] [arXiv:0709.3427v1] [preprint (ps)] [preprint (pdf)] [bib] [Scholar search]
  Cité par +/-

  1. A.H. Vahabie, M.M.R. Yousefi, B.N. Araabi, C. Lucas, S. Barghinia, and P.Ansarimehr. Mutual Information Based Input Selection in Neuro-Fuzzy Modeling for Short Term Load Forecasting of Iran National Power System. In Proceedings of the IEEE International Conference on Control and Automation (ICCA 2007), pages 2710-2715 , May 30 2007-June 1 2007.
  2. K. Hlavackova-Schindler, M. Palus, M. Vejmelka, and J. Bhattacharya. Causality detection based on information-theoretic approaches in time series analysis, Physics Reports, 441(1):1-46, 2007.
  3. L. Herrera, H. Pomares, I. Rojas, A. Guillen, A. Prieto, and O. Valenzuela. Recursive prediction for long term time series forecasting using advanced models. Neurocomputing, 70(16-18):2870-2880, October 2007.
  4. C. Gomez, R. Hornero, D. Abasolo, A. Fernandez, and J. Escudero. Analysis of the magnetoencephalogram background activity in alzheimer's disease patients with auto-mutual information. Computer Methods and Programs in Biomedicine, 87(3):239-247, 2007.
  5. A. Durand, O. Devos, C. Ruckebusch, and J. Huvenne. Genetic algorithm optimisation combined with partial least squares regression and mutual information variable selection procedures in near-infrared quantitative analysis of cotton-viscose textiles. Analytica Chimica Acta, 595(1-2):72-79, 2007.
  6. M. M. R. Yousefi, M. Mirmomeni, and C. Lucas. Input variables selection using mutual information for neuro fuzzy modeling with the application to time series forecasting. In Proceedings of the International Joint Conference on Neural Networks (IJCNN 2007), pages 1121-1126, Orlando, Florida (U.S.A.), August 2007.
  7. F. Corona, S. Sassu, Lorenzo and. Melis, and R. Baratti. Measure of topological relevance for soft sensing product properties. In Proceedings of the 8th IFAC International Symposium on Dynamics and Control of Process Systems (DYCOPS 2007), pages 175-180, June 2007.
  8. C. Tan, M. Li, and X. Qin. Random Subspace Regression Ensemble for Near-Infrared Spectroscopic Calibration of Tobacco Samples. Analytical Sciences, 24(5):647-653, May 2008.
  9. Q. Noirhomme, R.I. Kitney, and B. Macq. Single-Trial EEG Source Reconstruction for Brain–Computer Interface. IEEE Transactions on Biomedical Engineering, 55(5):1592-1601, May 2008.
• (6) 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] [Scholar search]
• (5) 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] [Scholar search]
• (4) 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] [Scholar search]
  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.
• (3) 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] [Scholar search]
  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.
• (2) 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] [Scholar search]
• (1) Self Organizing Map and Symbolic Data. Aïcha El Golli, Brieuc Conan-Guez et Fabrice Rossi. Journal of Symbolic Data Analysis, volume 2, numéro 1. November 2004.
  [lien éditeur] [hal] [arXiv:0709.3587v1] [pdf] [bib] [Scholar search]

Editoriaux

• (3) Progress in modeling, theory, and application of computational intelligence. Fabrice Rossi, Michael Biehl et Cecilio Angulo. Neurocomputing, volume 71, numéro 7-9, pages 1117-1119. March 2008.
  [lien éditeur] [bib] [Scholar search]
• (2) Advances in computational intelligence and learning. Michael Biehl, Erzsébet Merényi et Fabrice Rossi. Neurocomputing, volume 70, numéro 7-9, pages 1117-1119. March 2007.
  [lien éditeur] [bib] [Scholar search]
• (1) New Issues in Neurocomputing at ESANN 2005. Jochen J. Steil, Gavin Cawley et Fabrice Rossi. Neurocomputing, volume 69, numéro 7-9, pages 625-626. March 2006.
  [lien éditeur] [bib] [Scholar search]

Articles de vulgarisation

• (13) Java, .NET et les logiciels libres, 2.0. Fabrice Rossi. GNU/Linux Magazine France, numéro 87, pages 16-35. Octobre 2006.
  [lien éditeur] [bib] [Scholar search]
• (12) Audiophilie Linuxienne. Fabrice Rossi. Linux Pratique, numéro HS 4, pages 44-47. Avril/Mai 2006.
  [lien éditeur] [résumé] [bib] [Scholar search]
• (11) Java, .NET et les logiciels libres. Fabrice Rossi. GNU/Linux Magazine France, numéro 67, pages 8-17. Décembre 2004.
  [lien éditeur] [résumé] [pdf] [bib] [Scholar search]
• (10) La reconnaissance de gestes. Fabrice Rossi. GNU/Linux Magazine France, numéro 63, pages 58-69. Juillet/Août 2004.
  [lien éditeur] [résumé] [pdf] [bib] [Scholar search]
• (9) Découvrez les réseaux Bayésiens. Jean-Michel Marin et Fabrice Rossi. GNU/Linux Magazine France, numéro 60, pages 56-65. April 2004.
  [lien éditeur] [résumé] [pdf] [bib] [Scholar search]
• (8) L'ordinateur peut-il lire dans votre esprit ?. Fabrice Rossi. GNU/Linux Magazine France, numéro 58, pages 34-44. February 2004.
  [lien éditeur] [résumé] [pdf] [bib] [Scholar search]
• (7) Découvrez les algorithmes évolutionnaires. Fabrice Rossi. GNU/Linux Magazine France, numéro 57, pages 42-51. January 2004.
  [lien éditeur] [résumé] [pdf] [bib] [Scholar search]
• (6) L'intelligence artificielle des jeux de stratégie classiques. Eric Lacombe et Fabrice Rossi. GNU/Linux Magazine France, numéro 55, pages 18-31. November 2003.
  [lien éditeur] [résumé] [pdf] [bib] [Scholar search]
• (5) L'algorithme A* ou comment calculer rapidement un chemin optimal. Fabrice Rossi. GNU/Linux Magazine France, numéro 54, pages 32-41. October 2003.
  [lien éditeur] [résumé] [pdf] [bib] [Scholar search]
• (4) Recherche des chemins optimaux pour les jeux vidéo. Fabrice Rossi. GNU/Linux Magazine France, numéro 53, pages 50-58. September 2003.
  [lien éditeur] [résumé] [pdf] [bib] [Scholar search]
• (3) Filtrage de SPAM par méthodes probabilistes. Fabrice Rossi. Multi-System & Internet Security Cookbook, numéro 8, pages 74-80. July 2003.
  [lien éditeur] [résumé] [bib] [Scholar search]
• (2) L'intelligence collective : des fourmis dans votre Linux. Fabrice Rossi. GNU/Linux Magazine France, numéro 51, pages 66-75. June 2003.
  [lien éditeur] [résumé] [ps] [pdf] [bib] [Scholar search]
• (1) L'architecture de sécurité de Java. Fabrice Rossi. Multi-System & Internet Security Cookbook, numéro 7, pages 52-59. May 2003.
  [lien éditeur] [résumé] [ps] [pdf] [bib] [Scholar search]

Ouvrage collectif

• (1) GNU Scientific Library Reference Manual. Mark Galassi, Jim Davies, James Theiler, Brian Gough, Gerard Jungman, Michael Booth et Fabrice Rossi. Paru chez Network Theory Ltd., second edition, February 2003.
  [lien éditeur] [ps] [bib] [Scholar search]

Chapitres d'ouvrage collectif

• (6) The Unexpected Link: Dissemination of Health Information within Social Networks. Akos Rona-Tas, Stéphan Clémençon, Sandrine Blanchemanche, Fabrice Rossi et Charanpal Dhanjal. Dans "Networks in Social Policy Problems"A paraître chez Cambridge University Press.
  [bib] [Scholar search]
• (5) Constrained Variable Clustering and the Best Basis Problem in Functional Data Analysis. Fabrice Rossi et Yves Lechevallier. Dans "Classification and Multivariate Analysis for Complex Data Structures", pages 435-444, édité par Bernard Fichet, Domenico Piccolo, Rosanna Verde et Maurizio Vichi. Paru chez Springer Berlin / Heidelberg, March 2011.
  [lien éditeur] [preprint (pdf)] [bib] [Scholar search]
• (4) Median Topographic Maps for Biomedical Data Sets. Barbara Hammer, Alexander Hasenfuß et Fabrice Rossi. Dans "Similarity-Based Clustering (LNCS 5400)", pages 92-117, édité par Thomas Villlmann, Michael Biehl, Barbara Hammer et Michel Verleysen. Paru chez Springer Berlin / Heidelberg, 2009.
  [lien éditeur] [hal] [arXiv:0909.0638] [preprint (ps)] [preprint (pdf)] [bib] [Scholar search]
• (3) Advances in Feature Selection with Mutual Information. Michel Verleysen, Fabrice Rossi et Damien François. Dans "Similarity-Based Clustering (LNCS 5400)", pages 52-69, édité par Thomas Villlmann, Michael Biehl, Barbara Hammer et Michel Verleysen. Paru chez Springer Berlin / Heidelberg, 2009.
  [lien éditeur] [hal] [arXiv:0909.0635] [preprint (ps)] [preprint (pdf)] [bib] [Scholar search]
• (2) Clustering Dynamic Web Usage Data. Alzennyr Da Silva, Yves Lechevallier, Fabrice Rossi et Francisco De Carvalho. Dans "Innovative Applications in Data Mining", pages 71-82, édité par Nadia Nedjah, Luiza de Macedo Mourelle et Janusz Kacprzyk. Paru chez Springer Berlin / Heidelberg, 2009.
  [lien éditeur] [bib] [Scholar search]
• (1) Multi-Layer Perceptron and Symbolic Data. Fabrice Rossi et Brieuc Conan-Guez. Dans "Symbolic Data Analysis and the SODAS Software", pages 373-391, édité par Edwin Diday et Monique Noirhomme-Fraiture. Paru chez Wiley, January 2008.
  [lien éditeur] [hal] [arXiv:0802.0251] [preprint (ps)] [preprint (pdf)] [bib] [Scholar search]

Conférences internationales avec comité de lecture et publication des actes

• (50) Visual Mining of Epidemic Networks. Stéphan Clémençon, Hector De Arazoza, Fabrice Rossi et Viet-Chi Tran. In Cabestany, Joan and Rojas, Ignacio and Joya, Gonzalo, editors, Proceedings of 11th International Work-Conference on Artificial Neural Networks (IWANN 2011), pages 276-283, Malaga, Spain. June 2011.
  [lien éditeur] [hal] [pdf] [bib] [Scholar search]
• (49) Communication Challenges in Cloud K-means. Matthieu Durut et Fabrice Rossi. In Proceedings of XIXth European Symposium on Artificial Neural Networks (ESANN 2011), pages 387-392, Bruges, Belgium. April 2011.
  [pdf] [bib] [Scholar search]
• (48) Hierarchical clustering for graph visualization. Stéphan Clémençon, Hector De Arazoza, Fabrice Rossi et Viet-Chi Tran. In Proceedings of XIXth European Symposium on Artificial Neural Networks (ESANN 2011), pages 227-232, Bruges, Belgium. April 2011.
  [hal] [pdf] [bib] [Scholar search]
• (47) Seeing is believing: The importance of visualization in real-world machine learning applications. Alfredo Vellido, José Martín, Fabrice Rossi et Paulo Lisboa. In Proceedings of XIXth European Symposium on Artificial Neural Networks (ESANN 2011), pages 219-226, Bruges, Belgium. April 2011.
  [pdf] [bib] [Scholar search]
• (46) K-means on Azure. Matthieu Durut et Fabrice Rossi. In LCCC: NIPS 2010 Workshop on Learning on Cores, Clusters and Clouds, Whistler, Canada. December 2010.
  [lien éditeur] [pdf] [bib] [Scholar search]
• (45) Classification and regression based on derivatives: a consistency result. Nathalie Villa-Vialaneix et Fabrice Rossi. In II Simposio sobre Modelamiento Estadístico (invited conference), Valparaiso, Chile. December 2010.
  [slides] [bib] [Scholar search]
• (44) The structure of a gene network reveals 7 biological functions underlying eQTLs in pig. Laurence Liaubet, Nathalie Villa-Vialaneix, Adrien Gamot, Fabrice Rossi, Pierre Chérel et Magali San Cristobal. In Proceedings of the 9th World Congress on Genetics Applied to Livestock Production (WCGALP), Leipzig, Germany. August 2010.
  [lien éditeur] [pdf] [bib] [Scholar search]
• (43) Spatiotemporal sampling for trajectory streams. Mohamed K. El Mahrsi, Christine Potier, Georges Hébrail et Fabrice Rossi. In Sung Y. Shin and Sascha Ossowski and Michael Schumacher and Mathew J. Palakal and Chih-Cheng Hung, editors, Proceedings of the 2010 ACM Symposium on Applied Computing (SAC'10), pages 1627-1628, Sierre, Switzerland. March 2010.
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• (42) From Intracardiac Electrograms to Electrocardiograms: Models and Metamodels. Géraldine Ebrard, Miguel A. Fernández, Jean-Frédéric Gerbeau, Fabrice Rossi et Nejib Zemzemi. In Nicholas Ayache and Hervé Delingette and Maxime Sermesant, editors, Proceedings of the 5th International Conference on Functional Imaging and Modeling of the Heart (FIMH 2009), pages 524-533, Nice, France. June 2009.
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• (41) Topologically Ordered Graph Clustering via Deterministic Annealing. Fabrice Rossi et Nathalie Villa-Vialaneix. In Proceedings of XVIIth European Symposium on Artificial Neural Networks (ESANN 2009), pages 529-534, Bruges, Belgium. April 2009.
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• (40) Simultaneous Clustering and Segmentation for Functional Data. Bernard Hugueney, Georges Hébrail, Yves Lechevallier et Fabrice Rossi. In Proceedings of XVIIth European Symposium on Artificial Neural Networks (ESANN 2009), pages 281-286, Bruges, Belgium. April 2009.
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• (39) Supervised variable clustering for classification of NIR spectra. Catherine Krier, Michel Verleysen, Fabrice Rossi et Damien François. In Proceedings of XVIIth European Symposium on Artificial Neural Networks (ESANN 2009), pages 263-268, Bruges, Belgium. April 2009.
  [lien éditeur] [pdf] [bib] [Scholar search]
• (38) Patch Relational Neural Gas - Clustering of Huge Dissimilarity Datasets. Alexander Hasenfuß, Barbara Hammer et Fabrice Rossi. In Lionel Prevost and Simone Marinai and Friedhelm Schwenker, editors, Proceedings of the Third International Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR 08), pages 1-12, Paris, France. July 2008.
  [lien éditeur] [ps] [pdf] [bib] [Scholar search]
• (37) 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), Caserta, Italy. June 2008.
  [ps] [pdf] [bib] [Scholar search]
• (36) Recent advances in the use of SVM for functional data classification. Nathalie Villa-Vialaneix et Fabrice Rossi. In Frédéric Ferraty and Sophie Dabo-Niang, editors, Proceedings of 1rst International Workshop on Functional and Operatorial Statistics (IWFOS 2008), pages 273-280, Toulouse, France. June 2008.
  [lien éditeur] [ps] [pdf] [bib] [Scholar search]
• (35) Mining a medieval social network by kernel SOM and related methods. Nathalie Villa-Vialaneix, Fabrice Rossi et Quoc-Dinh Truong. In Proceedings of MASHS 2008 (Modèles et Apprentissages en Sciences Humaines et Sociales), Créteil, France. June 2008.
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• (34) Consistency of Derivative Based Functional Classifiers on Sampled Data. Fabrice Rossi et Nathalie Villa-Vialaneix. In Proceedings of XVIth European Symposium on Artificial Neural Networks (ESANN 2008), pages 445-450, Bruges, Belgium. April 2008.
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• (33) Construction and Analysis of Evolving Data Summaries: an Application on Web Usage Data. Alzennyr Da Silva, Yves Lechevallier, Fabrice Rossi et Francisco De Carvalho. In Luiza Mourelle, Nadia Nedjah and Janusz Kacprzyk, editors, Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007), pages 377-380, Rio de Janeiro, Brazil. October 2007.
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• (32) Topographic Processing of Relational Data. Barbara Hammer, Alexander Hasenfuß, Fabrice Rossi et Marc Strickert. In Proceedings of the 6th Workshop on Self-Organizing Maps (WSOM 07), Bielefeld, Germany. September 2007.
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• (31) Accelerating Relational Clustering Algorithms With Sparse Prototype Representation. Fabrice Rossi, Alexander Hasenfuß et Barbara Hammer. In Proceedings of the 6th Workshop on Self-Organizing Maps (WSOM 07), Bielefeld, Germany. September 2007.
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• (30) A comparison between dissimilarity SOM and kernel SOM for clustering the vertices of a graph. Nathalie Villa-Vialaneix et Fabrice Rossi. In Proceedings of the 6th Workshop on Self-Organizing Maps (WSOM 07), Bielefeld, Germany. September 2007.
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• (29) Clustering Strategies for Detecting Changes on Web Usage Data. Alzennyr Da Silva, Yves Lechevallier, Fabrice Rossi et Francisco De Carvalho. In Ivete Gomes, Dinis Pestana and Pedro Silva, editors, 56th Session of the International Statistical Institute (ISI 2007), Lisbon, Portugal. August 2007.
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• (28) Speeding Up the Dissimilarity Self-Organizing Maps by Branch and Bound. Brieuc Conan-Guez et Fabrice Rossi. In Sandoval, F.and Prieto, A. and Cabestany, J. and Graña, M., editors, Proceedings of 9th International Work-Conference on Artificial Neural Networks (IWANN 2007), pages 203-210, San Sebastian, Spain. June 2007.
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• (27) Model collisions in the dissimilarity SOM. Fabrice Rossi. In Proceedings of XVth European Symposium on Artificial Neural Networks (ESANN 2007), pages 25-30, Bruges, Belgium. April 2007.
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• (26) Feature clustering and mutual information for the selection of variables in spectral data. Catherine Krier, Fabrice Rossi, Damien François et Michel Verleysen. In Proceedings of XVth European Symposium on Artificial Neural Networks (ESANN 2007), pages 157-162, Bruges, Belgium. April 2007.
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• (25) A functional approach to variable selection in spectrometric problems. Fabrice Rossi, Damien François, Vincent Wertz et Michel Verleysen. In S. Kollias, A. Stafylopatis, W. Duch, and E. Oja, editors, Artificial Neural Networks (Proceedings of 16th International Conference on Artificial Neural Networks, ICANN 2006), pages 11-20, Athens, Greece. September 2006.
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• (24) Dissimilarities for Web Usage Mining. Fabrice Rossi, Francisco De Carvalho, Yves Lechevallier et Alzennyr Da Silva. In V. Batagelj, H.-H. Bock, A. Ferligoj and A. Žiberna, editors, Data Science and Classification (Proceedings of IFCS 2006), pages 39-46, Ljubljana, Slovenia. July 2006.
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• (23) Visualization Methods for Metric Studies. Fabrice Rossi. In Proceedings of the International Workshop on Webometrics, Informetrics and Scientometrics, pages 356-366, Nancy, France. May 2006.
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• (22) Visual Data Mining and Machine Learning. Fabrice Rossi. In Proceedings of XIVth European Symposium on Artificial Neural Networks (ESANN 2006), pages 251-264, Bruges, Belgium. April 2006.
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• (21) 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.
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• (20) A Fast Algorithm for the Self-Organizing Map on Dissimilarity Data. Brieuc Conan-Guez, Fabrice Rossi et Aïcha El Golli. In Proceedings of the 5th Workshop on Self-Organizing Maps (WSOM 05), pages 561-568, Paris, France. September 2005.
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  Cité par +/-

  1. M. Cottrell, B. Hammer, A. Hasenfuß and T. Villmann, Batch and Median Neural Gas, Neural Networks, 19(6-7):762-771, July-August, 2006.
  2. B. Hammer, A. Hasenfuß, F.-M. Schleif, and T. Villmann. Supervised batch neural gas. In F. Schwenker and S. Marinai, editors, Artificial Neural Networks in Pattern Recognition (Second IAPR Workshop, ANNPR 2006), volume 4087 of Lecture Notes in Computer Science, pages 33-45, Ulm (Germany), August-September 2006. Springer.
  3. B. Hammer, A. Hasenfuß, F.-M. Schleif, and T. Villmann. Supervised median clustering. In C. H. Dagli, A. L. Buczak, D. L. Enke, M. Embrechts, and O. Ersoy, editors, Proceedings of the Artificial Neural Networks in Engineering Conference (ANNIE 2006), pages 623-632, St. Louis, MO (U.S.A.), November 2006.
  4. A. Hasenfuß, B. Hammer, F.-M. Schleif, and T. Villmann. Neural gas clustering for dissimilarity data with continuous prototypes. 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 539-546, San Sebastián (Spain), June 2007. Springer.
  5. B. Hammer and A. Hasenfuß. Relational neural gas. In Proceedings of the 30th Annual German Conference on AI, KI 2007, volume 4667 of Lecture Notes in Computer Science, pages 190-204, Osnabrück (Germany), September 2007. Springer.
  6. A. Hasenfuß and B. Hammer. Relational topographic maps. In Proceedings of the 7th International Symposium on Intelligent Data Analysis, IDA 2007, volume 4723 of Lecture Notes in Computer Science, pages 93-105, Ljubljana (Slovenia), September 2007. Springer.
  7. B. Hammer, A. Hasenfuß, F.-M. Schleif, T. Villmann, M. Strickert, and U. Seiffert. Intuitive clustering of biological data. In Proceedings of the International Joint Conference on Neural Networks (IJCNN 2007), pages 1877-1882, Orlando, Florida (U.S.A.), August 2007.
• (19) Classification in Hilbert Spaces with Support Vector Machine. Fabrice Rossi et Nathalie Villa-Vialaneix. In Proceedings of the XIth International Symposium on Applied Stochastic Models and Data Analysis (ASMDA 2005), pages 635-642, Brest, France. May 2005.
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  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.
• (18) Support Vector Machine For Functional Data Classification. Nathalie Villa-Vialaneix et Fabrice Rossi. In Proceedings of XIIIth European Symposium on Artificial Neural Networks (ESANN 2005), pages 467-472, Bruges, Belgium. April 2005.
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  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.
• (17) Usage Guided Clustering of Web Pages with the Median Self Organizing Map. Fabrice Rossi, Aïcha El Golli et Yves Lechevallier. In Proceedings of XIIIth European Symposium on Artificial Neural Networks (ESANN 2005), pages 351-356, Bruges, Belgium. April 2005.
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• (16) 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.
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  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.
• (15) 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] [Scholar search]
• (14) 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.
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  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.
• (13) 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.
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  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.
• (12) 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.
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• (11) 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.
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• (10) Multi-layer Perceptron on Interval Data. Fabrice Rossi et Brieuc Conan-Guez. In K. Jajuga, A. Sokolowski, H.-H. Bock, editors, Classification, Clustering, and Data Analysis (IFCS 2002), pages 427-434, Cracow, Poland. July 2002.
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  Cité par +/-

  1. R. E. Patiño-Escarcina, B. R. Callejas Bedregaland, and A. Lyra. Interval computing in neural networks: One layer interval neural networks. In Proceeding of 7th International Conference on Information Technology, volume 3356 of Lecture Notes in Computer Science, Hyderabad (India), December 2004.
  2. H. Hamdan and G. Govaert. CEM algorithm for imprecise data. application to flaw diagnosis using acoustic emission, in Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, volume 5, pages 4774-4779, October 2004.
  3. H. Hamdan and G. Govaert. Int-EM-CEM algorithm for imprecise data. comparison with the CEM algorithm using monte carlo simulations, in Proceedings of the IEEE Conference Cybernetics and Intelligent Systems, volume 1, pages 410-415, Singapore, December 2004.
  4. H. Hamdan and G. Govaert. Mixture model clustering of uncertain data, in Proceedings of the 14th IEEE International Conference on Fuzzy Systems (FUZZ'05), pages 879-884, Reno, Nevada, USA, May 2005.
  5. A. Appice, C. D'Amato, F. Esposito, and D. Malerba. Classification of symbolic objects: A lazy learning approach, Intelligent Data Analysis, 10(4):301-324, 2006.
  6. A. P. Duarte Silva and P. Brito. Linear discriminant analysis for interval data, Computational Statistics, 21(2):289-308, June 2006.
  7. A. Munoz San Roque, C. Maté, J. Arroyo, and Á. Sarabia. iMLP : Applying multi-layer perceptrons to interval-valued data, Neural Processing Letters, 2007.
  8. F. C. D. Silva, F. d. A. de Carvalho, R. M. C. R. de Souza, and J. Q. Silva. A modal symbolic classifier for interval data. In I. King, J. Wang, C. Laiwan, and D. Wang, editors, Proceedings of the 13th International Conference, ICONIP 2006, volume 4233, pages 50-59, Hong Kong (China), October 2006. Springer.
• (9) 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.
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• (8) 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.
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  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.
• (7) Expert Constrained Clustering: A Symbolic Approach. Fabrice Rossi et Frédérick Vautrain. In Djamel A. Zighed, Jan Komorowski and Jan Zytkow, editors, Principles of Data Mining and Knowledge Discovery, pages 605-612, Lyon, France. September 2000.
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  Cité par +/-

  1. Y. Huo, F. Azuaje, P. McCullagh, and R. Harper. Semi-supervised clustering models for clinical risk assessment. In Proceedings of the Sixth IEEE Symposium on BioInformatics and BioEngineering (BIBE 2006), pages 243-250, October 2006.
• (6) Geometrical Selection of Important Inputs with Feedforward Neural Networks. Fabrice Rossi. In Pearson, D. W. and Steele, N. C. and Albrecht, R. F., editors, Int. Conf. on Artificial Neural Nets and Genetic Algorithms, Norwich, United Kingdom. April 1997.
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• (5) Attribute suppression with multi-layer perceptron. Fabrice Rossi. In CESA Multiconference, volume Symposium on Robotics and Cybernetics, pages 542-547, Lille, France. July 1996. IMACS
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  Cité par +/-

  1. B. Jeong and H. Cho. Feature selection techniques and comparative studies for large-scale manufacturing processes. The International Journal of Advanced Manufacturing Technology, 28(9):1006-1011, April 2006.
  2. M. Yacoub. Techniques d'élagage et sélection de variables. In Y. Bennani, editor, Apprentissage connexionniste, Informatique et Systèmes d'information, chapter 9, pages 249-277. Hermes Science / Lavoisier, 2006.
  3. P. Leray and P. Gallinari. Feature selection with neural networks. Behaviormetrika, 26(1):145-166, 1999. Special issue on Analysis of-Knowledge Representation in Neural Network Models.
• (4) Second Differentials in Arbitrary FeedForward Neural Networks. Fabrice Rossi. In Int. Conf. on Neural Networks, volume I, pages 418-423, Washington, USA. June 1996. IEEE
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• (3) Generic Back-Propagation in Arbitrary Feedforward Neural Networks. Cédric Gégout, Bernard Girau et Fabrice Rossi. In Pearson, D. W. and Steele, N. C. and Albrecht, R. F., editors, Int. Conf. on Artificial Neural Nets and Genetic Algorithms, pages 168-171, Alès, France. April 1995.
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• (2) Geometrical Initialization, Parametrization and Control of Multilayer Perceptrons: Application to Function Approximation. Fabrice Rossi et Cédric Gégout. In Int. Conf. on Neural Networks, volume I, pages 546-550, Orlando, Florida, USA. June 1994. IEEE
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  Cité par +/-

  1. M. Fernandez-Redondo and C. Hernandez-Espinosa. A comparison among weight initialization methods for multilayer feedforward networks. In Proceedings of the International Joint Conference on Neural Networks (IJCNN'00), volume 4, pages 543-548, Como, Italy, July 2000.
• (1) NSK, an Object-Oriented Simulator Kernel for Arbitrary Feedforward Neural Networks. Cédric Gégout, Bernard Girau et Fabrice Rossi. In Int. Conf. on Tools with Artificial Intelligence, pages 93-104, New Orleans, Lousiana, USA. November 1994. IEEE
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Conférences nationales avec comité de lecture et publication des actes

• (20) Méthode de classification organisée pour les recherche de communautés dans les réseaux sociaux. Nathalie Villa-Vialaneix et Fabrice Rossi. In Actes des 41èmes Journées de Statistique, SFdS, Journée satellite STID (conférence invitée), Bordeaux, France. Mai 2009.
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• (19) Estimation de redondance pour le clustering de variables spectrales. Damien François, Catherine Krier, Fabrice Rossi et Michel Verleysen. In Actes des 10èmes journées Européennes Agro-industrie et Méthodes statistiques (Agrostat 2008), pages 55-61, Louvain-la-Neuve, Belgique. Janvier 2008.
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• (18) Estimation de redondance conditionnelle par plus proches voisins, application au clustering de variables spectrales. Damien François, Catherine Krier, Fabrice Rossi et Michel Verleysen. In Actes de la conférence Chimiométrie 2007, pages 43-46, Lyon, France. Novembre 2007.
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• (17) Groupement de données évolutives dans la fouille d'usage du Web. Alzennyr Da Silva, Yves Lechevallier, Fabrice Rossi et Francisco De Carvalho. In Actes des 39èmes Journées de Statistique de la SFdS, Angers, France. Juin 2007.
  [ps] [pdf] [bib] [Scholar search]
• (16) Classifications non supervisées de données évolutives : application au Web Usage Mining. Alzennyr Da Silva, Yves Lechevallier, Fabrice Rossi et Francisco De Carvalho. In Atelier 4 : Flux de données, 7ème journées Extraction et Gestion des Connaissances (EGC 2007), pages 31-40, Namur, Belgique. Janvier 2007.
  [ps] [pdf] [bib] [Scholar search]
• (15) Construction et analyse de résumés de données évolutives : application aux données d'usage du Web. Alzennyr Da Silva, Yves Lechevallier, Fabrice Rossi et Francisco De Carvalho. In Actes des 7ème journées Extraction et Gestion des Connaissances (EGC 2007), volume II, pages 539-544, Namur, Belgique. Janvier 2007.
  [ps] [pdf] [bib] [Scholar search]
• (14) Un algorithme efficace pour les cartes auto-organisatrices de Kohonen appliquées aux tableaux de dissimilarités. Brieuc Conan-Guez, Fabrice Rossi et Aïcha El Golli. In M. Nadif et F.-X. Jollois, editors, Actes des treizièmes rencontres de la Société Francophone de Classification, Metz, France. September 2006.
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• (13) SVM fonctionnels par interpolation spline. Nathalie Villa-Vialaneix et Fabrice Rossi. In Actes des 38ièmes Journées de Statistique de la SFDS, Clamart, France. May/June 2006.
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• (12) Comparaison de dissimilarités pour l'analyse de l'usage d'un site web. Fabrice Rossi, Francisco De Carvalho, Yves Lechevallier et Alzennyr Da Silva. In G. Ritschard and C. Djeraba, editors, Actes des 6ème journées Extraction et Gestion des Connaissances (EGC 2006), Revue des Nouvelles Technologies de l'Information (RNTI-E-6), pages 409-414, Villeneuve d'Ascq, France. Janvier 2006.
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• (11) Sélection de groupes de variables spectrales par information mutuelle grâce à une représentation spline. Fabrice Rossi, Damien François, Vincent Wertz et Michel Verleysen. In Actes de la conférence Chimiométrie 2005, pages 52-55, Villeneuve d'Ascq, France. Décembre 2005.
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• (10) Visualisation de la perception d'un site web par ses utilisateurs. Fabrice Rossi, Yves Lechevallier et Aïcha El Golli. In S. Pinzon and N. Vincent, editors, Actes des 5ème journées Extraction et Gestion des Connaissances (EGC 2005), Revue des Nouvelles Technologies de l'Information (RNTI-E-3), pages 563-574, Paris, France. Janvier 2005.
  [ps] [pdf] [bib] [Scholar search]
  Cité par +/-

  1. T. Carron, J.-C. Marty, L. France, and J.-M. Heraud. Preparing an observed pedagogical experiment, in Proceedings of Cognition and Exploratory Learning in Digital Age (CELDA 2005), pages 526-531, Porto, Portugal, December 2005. IADIS.
  2. G.-C. Loghin, J.-C. Marty, and T. Carron. A method for enabling a better comprehension of user behavior, in Proceedings of Cognition and Exploratory Learning in Digital Age (CELDA 2005), pages 349-352, Porto, Portugal, December 2005. IADIS.
  3. T. Carron, J.-C. Marty, J.-M. Heraud, and L. France. Préparation d'une expérimentation pédagogique en vue d'observation, in 13ème Rencontres interdisciplinaires sur les systèmes complexes naturels et artificiels, Rochebrune (France), Janvier 2006.
• (9) Sélection de variables spectrales par information mutuelle multivariée pour la construction de modèles non-linéaires. Amaury Lendasse, Damien François, Fabrice Rossi, Vincent Wertz et Michel Verleysen. In Actes de la conférence Chimiométrie 2004, pages 44-47, Paris, France. Décembre 2004.
  [pdf] [bib] [Scholar search]
• (8) Une application des cartes topologiques auto-organisatrices à l'analyse des fichiers Logs. Aïcha El Golli, Fabrice Rossi, Brieuc Conan-Guez, Doru Tanasa, Brigitte Trousse et Yves Lechevallier. In Actes des Onzièmes journées de la Société Francophone de Classification, pages 181-184, Bordeaux, France. Septembre 2004.
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• (7) 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.
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• (6) 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.
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• (5) 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] [Scholar search]
  Cité par +/-

  1. L. Ferré and A.-F. Yao, Smoothed functional inverse regression, Statistica Sinica 15(2005), 665-683.
• (4) Traitement symbolique de contraintes expertes en classification automatique. Fabrice Rossi et Frédérick Vautrain. In F. Le Ber, J.F. Mari, A. Napoli, and A. Simon, editors, Actes des Septièmes journées de la Société Francophone de Classification, pages 221-227, Nancy, France. September 1999. SFC'99
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• (3) Deux méthodes de segmentation sur un tableau de données symboliques. Jean-Pascal Aboa Yapo, Barnabé Tang Ahanda, Richard Emilion et Fabrice Rossi. In Actes des Sixièmes journées de la Société Francophone de Classification, Montpellier, France. September 1998. SFC'98
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• (2) NSK, un noyau pour la simulation orientée objet de réseaux de neurones. Cédric Gégout, Bernard Girau et Fabrice Rossi. In Journées internationales sur Les Réseaux Neuromimétiques et leurs Applications, pages 123-131, Marseille, France. December 1994. Neuro-Nîmes
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• (1) Initialisation des Réseaux de Neurones Non Récurrents à coefficients réels par Algorithmes Evolutionnistes. Cédric Gégout et Fabrice Rossi. In Journées internationales sur Les Réseaux Neuromimétiques et leurs Applications, pages 416-424, Marseille, France. December 1994. Neuro-Nîmes
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Rapports

• (6) Un modèle semi-paramétrique neuronal pour la régression et la discrimination sur données fonctionnelles. Fabrice Rossi et Brieuc Conan-Guez. October 2003. Rapport numéro 0338 (CEREMADE) Soumis à Revue de Statistique Appliquée
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• (5) Estimation consistante des paramètres d'un modèle semi-paramétrique pour des données fonctionnelles discrétisées aléatoirement. Fabrice Rossi et Brieuc Conan-Guez. October 2003. Rapport numéro 0334 (CEREMADE) Soumis à Comptes Rendus de l'Académie des Sciences
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• (4) Functional Multi-Layer Perceptron: a Nonlinear Tool for Functional Data Analysis. Fabrice Rossi et Brieuc Conan-Guez. September 2003. Rapport numéro 0331 (CEREMADE) Soumis à Neural Networks
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• (3) Functional Multi Layer Perceptrons. Fabrice Rossi, Brieuc Conan-Guez et François Fleuret. December 2001. Rapport numéro 0134 (CEREMADE)
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• (2) Second Differentials in Arbitrary Feed-Forward Neural Networks. Fabrice Rossi. September 1996. Rapport numéro THOMSON-CSF/AIRSYS/RDTE-594/96 (Thomson-CSF/AIRSYS)
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• (1) A General Feed-Forward Neural Network Model. Cédric Gégout, Bernard Girau et Fabrice Rossi. May 1995. Rapport numéro NC-TR-95-041 (NeuroCOLT)
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