Diday Edwin - CV

CEREMADE

Diday Edwin

Professeur émérite

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Biographie

E. Diday is now Emeritus Professor of Exceptional Class at the Paris Dauphine University in Computer science and Applied Mathematics (CEREMADE Laboratory). He was the Scientific Manager of two EUROSTAT projects SODAS and ASSO (17 teams from 9 European countries) until 2003.  Until 2013 he was involved in an NSF (USA) grant on Symbolic data analysis (SDA) and he is now involved until 2019 with Beihang University (China) in a "NFSC’s Major International Joint Research Project on “Statistical Modeling Methods of Massive High Dimensional Mixed Data”. He is author or editor of 14 books and of more than 50 papers in journals. He has directed 58 Doctoral theses. He is one of the founders and president of the Francophone Society of Classification. His most recent contribution concerns SDA used in service inspection of reinforced concrete of EDF nuclear plants (2012),  PCA for symbolic data (2013), hospital pathways in the management of cancer, (2013), in SDA a Factorial Approach Based on Fuzzy Coded Data (2014), Strategies evaluation in environmental conditions by symbolic data analysis applied in epidemiology to trachoma (2015), from the Symbolic Data Analysis of Virtual Faces to a Smiles Machine (2016), and an overview on Thinking by classes in Data Science and the SDA paradigm (2016). Its last publication is a book on SDA published by the TECHNIP Editor (2018, 435 ages) and a John Wiley book on Clustering methodology in SDA (2019) . He is the founder of the Dynamical Clustering Method (opening the path to local models), of the Pyramidal Clustering (for spatial representation of overlapping clusters), of the Symbolic Data Analysis paradigm (where classes are considered as new units). He is awarded laureate of the Montyon Price given by the French Academy of Sciences.

Publications

Articles

Diday E. (2016), Thinking by classes in Data Science: the symbolic data analysis paradigm, Wiley Interdisciplinary Reviews. Computational Statistics, vol. 8, n°5, p. 172–205

Ochs M., Diday E., Afonso F. (2016), From the Symbolic Analysis of Virtual Faces to a Smiles Machine, IEEE Transactions on Cybernetics, vol. 46, n°2, p. 401 - 409

Guinot C., Haddad R., Malvy D., Schémann J-F., Diday E., Afonso F. (2015), Strategies evaluation in environmental conditions by symbolic data analysis: application in medicine and epidemiology to trachoma, Advances in Data Analysis and Classification, vol. 9, n°1, p. 107-119

Billard L., Chédin A., Diday E., Vrac M. (2012), Copula analysis of mixture models, Computational Statistics, vol. 27, n°3, p. 427-457

Diday E., Makosso Kallyth S. (2012), Adaptation of interval PCA to symbolic histogram variables, Advances in Data Analysis and Classification, vol. 6, n°2, p. 147-159

Billard L., Diday E., Douzal-Chouakria A. (2011), Principal component analysis for interval-valued observations, Statistical Analysis and Data Mining, vol. 4, n°2, p. 229-246

Quantin C., BIllard L., Touati M., Andreu N., Cottin Y., Zeller M., Afonso F., Battaglia G., Seck D., Le Teuff G., Diday E. (2011), Classification and Regression Trees on Aggregate Data Modeling: An Application in Acute Myocardial Infarction, Journal of Probability and Statistics, vol. 2011, p. 523937

Crémona C., Cury A., Diday E. (2010), Application of symbolic data analysis for structural modification assessment, Engineering Structures, vol. 32, n°3, p. 762-775

Diday E. (2008), Spatial classification, Discrete Applied Mathematics, vol. 156, n°8, p. 1271-1294

Billard L., Diday E. (2006), Descriptive Statistics for Interval-valued Observations in the presence of Rules, Computational Statistics, vol. 21, n°2, p. 187-210

Winsberg S., Groenen P., Diday E., Rodriguez O. (2006), I-scal : Multidimensional scaling of interval dissimilarities, Computational Statistics & Data Analysis, vol. 51, n°1, p. 360-378

Chédin A., Diday E., Vrac M. (2005), Clustering a Global Field of Atmospheric Profiles by Mixture Decomposition of Copulas, Journal of Atmospheric and Oceanic Technology, vol. 22, n°10, p. 1145-1459

Diday E., Vrac M. (2005), Mixture decomposition of distributions by copulas in the symbolic data analysis framework, Discrete Applied Mathematics, vol. 147, n°1, p. 27-41

Chédin A., Diday E., Vrac M. (2004), Décomposition de mélange de distributions et application à des données climatiques, Revue de statistique appliquée, vol. 52, n°1, p. 67-96

Diday E., Limam M., Winsberg S. (2003), Symbolic Class Description with Interval Data, Journal of Symbolic Data Analysis, vol. 1, n°1, p. 10

Billard L., Diday E. (2003), From the statistics of data to the statistics of knowledge: Symbolic data analysis., Journal of the American Statistical Association, vol. 98, n°462, p. 470-487

Diday E., Emilion R. (2003), Maximal and stochastic Galois Lattices, Discrete Applied Mathematics, vol. 2, n°127, p. 271-284

Diday E., Esposito F. (2003), An introduction to symbolic data analysis and the SODAS software, Intelligent Data Analysis, vol. 7, n°6, p. 583-601

Gettler-Summa M., Diday E., Ho T. (1988), Generating rules for expert systems from observations, Pattern Recognition Letters, vol. 7, n°5, p. 265-271

Ouvrages

Billard L., Diday E. (2019), Clustering Methodology for Symbolic Data John Wiley & Sons, Ltd, 352 p.

Afonso F., Diday E., Toque C. (2018), Data Science par Analyse des Données Symboliques, Paris: Editions Techniques, 435 p.

Diday E., Noirhomme-Fraiture M. (2008), Symbolic Data Analysis and the SODAS Software, Chichester: Wiley, 457 p.

Chapitres d'ouvrage

Touati M., Djedour M., Diday E. (2011), Synthesis of Objects, in Touati, Myriam, Statistical Learning and Data Science Taylor & Francis, p. 243

Diday E. (2011), Principal Component Analysis for Categorical Histogram Data: Some Open Directions of Research, in Vichi, Maurizio, Classification and Multivariate Analysis for Complex Data Structures, Berlin: Studies in Classification, Data Analysis, and Knowledge Organization, p. 473

Diday E., Billard L. (2006), Symbolic Data Analysis : Conceptual statistics and data Mining, in Diday E. ; Billard L., Symbolic Data Analysis, Chichester (England) Hoboken (NJ): Wiley Series in Computational Statistics, p. 1-321

Diday E., Murthy N. (2005), Symbolic Data Clustering, in Wang, John, Encyclopedia of Data Warehousing and Mining Information Science Reference, p. 1382

Diday E., Goupil-Testu F., Moult R., Touati M. (2000), Census Data from the Office for National Statistics, in Diday, Edwin, Analysis of Symbolic Data. Exploratory Methods for Extracting Statistical Information from Complex Data, Berlin: Springer, p. 425

Diday E., Simon J. (1980), Clustering Analysis, in Fu, King-Sun, Digital pattern recognition, Berlin: Springer, p. 234

Communications avec actes

Afonso F., Courtois A., Diday E., Genest 0., Orcesi A. (2012), In-service inspection of reinforced concrete cooling towers – EDF's feedback, in Strauss, Alfred, Third International Symposium on Life-Cycle Civil Engineering (IALCCE'12), Vienne, CRC Press, 1102-1109 p.

Balbo F., Diday E., Pinson S., Saunier J. (2009), De l’utilisation de l’analyse de données symboliques dans les systèmes multi-agents, in Gançarski, Pierre, Extraction et gestion des connaissances (EGC'2009), Actes, Strasbourg, 27 au 30 janvier 2009, Strasbourg, Cépaduès Editions, 139-150 p.

Afonso F., Diday E., Rahal M., Touati M. (2008), Le logiciel SODAS : avancées récentes Un outil pour analyser et visualiser des données symboliques, in Brigitte Trousse, Fabrice Guillet, Extraction et gestion des connaissances EGC 2008, Sophia Antipolis, Cépaduès Editions, 239-240 p.

Caillou P., Diday E. (2005), Analyse de données symboliques et graphe de connaissances d’un agent, in Vincent, Nicole, Extraction et gestion des connaissances (EGC'2005), Actes des cinquièmes journées Extraction et Gestion des Connaissances, Paris, France, 18-21 janvier 2005, Paris, Cépaduès Editions, 643-648 p.

Diday E. (2005), De la statistique des données à la statistique des connaissances : avancées récentes en Analyse des Données Symboliques, in Vincent, Nicole, Extraction et gestion des connaissances (EGC'2005), Actes des cinquièmes journées Extraction et Gestion des Connaissances, Paris, France, 18-21 janvier 2005, Paris, Cépaduès Editions, 703 p.

Diday E., Mballo C. (2005), Arbres de décision sur des données de type intervalle : évaluation et comparaison, in Vincent, Nicole, Extraction et gestion des connaissances (EGC'2005), Actes des cinquièmes journées Extraction et Gestion des Connaissances, Paris, France, 18-21 janvier 2005, Paris, Cépaduès Editions, 67-78 p.

Diday E., Pak K., Rahal M. (2005), Elagage et aide à l'interprétation symbolique et graphique d'une pyramide, in Vincent, Nicole, Extraction et gestion des connaissances (EGC'2005), Actes des cinquièmes journées Extraction et Gestion des Connaissances, Paris, France, 18-21 janvier 2005, Paris, Cépaduès Editions, 135-146 p.

Afonso F., Diday E. (2005), Extension de l'algorithme Apriori et des règles d'association aux cas des données symboliques diagrammes et intervalles, in Vincent, Nicole, Extraction et gestion des connaissances (EGC'2005), Actes des cinquièmes journées Extraction et Gestion des Connaissances, Paris, France, 18-21 janvier 2005, Paris, Cépaduès Editions, 483-494 p.

Diday E., Goupil-Testu F., Touati M., Van der Veen H. (2000), Analyse symbolique de données financières, in Dagnelie, Pierre, XXXIIèmes journées de statistique, ASU 2000, Fès, Groupe de recherche en statistique de Fès, 917 p.

Diday E. (1999), A wider domain of symbolic analysis to prepare decisions : the SODAS project, in Zopounidis, Constantin, Integrating technology & human decisions : global bridges into the 21st century. Volume II, Athènes, New Technologies Publications, 1195-1197 p.

Cucumel G., Diday E. (1988), Compatibility and consensus in numerical taxonomy, in , 9th International Conference on Pattern Recognition, 1988. Proceedings, Rome, IEEE - Institute of Electrical and Electronics Engineers, 1059-1061 (vol.2) p.

Communications sans actes

Diday E., Fablet C., Bougeard S., Toque C. (2010), Etudes des lésions pulmonaires chez le porc : una analyse symbolique sur des concepts issus de l'approche classique, 42èmes Journées de Statistique, Marseille, France

Diday E., Makosso Kallyth S. (2010), Analyse en axes principaux de variables symboliques de type histogramme, 42èmes Journées de Statistique, Marseille, France

Crémona C., Cury A., Diday E. (2009), A methodology based on symbolic data analysis for structural damage assessment, 3rd International Operational Modal Analysis Conference: IOMAC, Ancone, Italie

Charlton J., Diday E., Goupil-Testu F., Touati M. (1999), Le logiciel Sodas pour l'analyse des données symboliques : une application à des données du recensement du Royaume Uni., 7èmes rencontres de la Société francophone de classification., Nancy, France

Diday E., Emilion R., Goupil-Testu F. (1995), Histogramme de capacités en analyse des données symboliques, 3èmes rencontres de la Société francophone de classification, Namur, Belgique

Actes d'une conférence

Diday E., Saporta G., LECHEVALLIER Y., Guan R., Wang H. (2020), Advances in Theory and applications of High Dimensional and Symbolic Data Analysis, in , Paris, Hermann, 216 p

Prépublications / Cahiers de recherche

Billard L., Diday E. (2004), Symbolic Data Analysis: Definition and Examples, Paris, Cahiers du CEREMADE, 62 p.

Diday E., Goupil-Testu F., Touati M. (2004), Etude de la performance d'un portefeuille en fonction des actions qui le composent, Paris, Cahiers du CEREMADE, 15 p.

Diday E. (2001), Knowledge Discovery from Symbolic Data and the SODAS Software, Paris, Cahiers du CEREMADE, 34 p.

Diday E., Vrac M. (2001), Description symbolique de classes, Paris, Cahiers du CEREMADE

Diday E. (2001), A Generalisation of the Mixture Decomposition Problem in the Symbolic Data Analysis Framework, Paris, Cahiers du CEREMADE, 14 p.

Diday E., Polaillon G. (1996), Galois Lattices Construction and Application in Symbolic Data Analysis, Paris, Cahiers du CEREMADE

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