CEREMADE
Bertrand Patrice
Associate Professor
Biography
Patrice Bertrand is an Associate Professor at university Paris-Dauphine and a member of CEREMADE, a research centre in Decision Mathematics at university Paris-Dauphine. He currently leads the ISF master diploma which is a professional formation specialised in statistical and financial engineering (ISF). He received a Ph.D. degree in Applied Mathematics from university Paris-Dauphine. From 1992 to 2013, he was an external research collaborator at INRIA-Rocquencourt (french National Research Institute for the digital sciences). His research interests focus on ordered sets, theory of cluster analysis, more particularly multi-level clustering structures that include both the classical hierarchical model and cluster models allowing overlapping clusters, together on cluster validation based on stability measures. He has authored a number of research papers in international journals and conferences. He gave invited talks in conferences and workshops devoted to data mining, and was recently the organizer of the Invited Paper Session entitled "Recent advances in cluster validation" during the ISI 2015 conference (60th Word Statistics Congress). He was a member of several scientific committees of national and international conferences that deal with Data-Mining. He was the scientific secretary of the Francophone Society of Classification (SFC) from 1992 to 1993, the IFCS Council representative of SFC from 2007 to 2010, and the scientific secretary of the International Federation of Classification Societies (IFCS) from 2011 to 2013. He has also served as reviewer of many conferences and international journals such as Pattern Recognition, Journal of Classification, Statistical Analysis and Data Mining, french Review of New Information Technologies (RNTI), Computational Statistics & Data Analysis (CSDA).
Publications
Articles
Bertrand P., Diatta J. (2024), An interval convexity-based framework for multilevel clustering with applications to single-linkage clustering, Discrete Applied Mathematics, vol. 342, p. 38-63 
Bertrand P., Diatta J. (2017), Multilevel clustering models and interval convexities, Discrete Applied Mathematics, vol. 222, n°11, p. 54-66
Carvalho F., Bertrand P., Simões E. (2016), Batch SOM algorithms for interval-valued data with automatic weighting of the variables, Neurocomputing, vol. 182, p. 66-81
Bertrand P., Diatta J. (2013), Prepyramidal clustering and Robinsonian dissimilarities: one‐to‐one correspondences, Wiley Interdisciplinary Reviews. Data Mining and Knowledge Discovery, vol. 3, n°4, p. 290-297
Bertrand P., Diatta J. (2013), Prepyramidal clustering and Robinsonian dissimilarities: one-to-one correspondences, Wiley Interdisciplinary Reviews. Data Mining and Knowledge Discovery, vol. 3, n°4, p. 290-297
Bertrand P. (2010), Classifications en classes recouvrantes ou non, et leurs dissimilarités, Mathematiques et sciences humaines, vol. 2, n°190, p. 59-87
Bertrand P. (2008), Systems of sets such that each set properly intersects at most one other set - Application to cluster analysis, Discrete Applied Mathematics, vol. 156, n°8, p. 1220-1236
Bertrand P., Bel Mufti G. (2006), Loevinger's measures of rule quality for assessing cluster stability, Computational Statistics & Data Analysis, vol. 50, n°4, p. 992-1015
Csernel M., Bertrand P. (2005), Comparaison de manuscrits sanskrits (édition critique et classification), MODULAD, n°33, p. 1-20
Bertrand P., Janowitz M. (2003), The k-weak hierarchical representations: an extension of the indexed closed weak hierarchies, Discrete Applied Mathematics, vol. 127, n°2, p. 199-220
Bertrand P., Janowitz M. (2002), Pyramids and Weak Hierarchies in The Ordinal Model for Clustering, Discrete Applied Mathematics, vol. 122, n°1-3, p. 55-81
Bertrand P. (2000), Set Systems and Dissimilarities, European Journal of Combinatorics, vol. 21, n°6, p. 727-743
Chapitres d'ouvrage
Bertrand P., Diatta J. (2014), Weak Hierarchies: A Central Clustering Structure, in Pardalos, Panos M., Clusters, Orders, and Trees: Methods and Applications, Berlin: Springer, p. 211-230
Bertrand P., Bel Mufti G. (2008), Stability measures for assessing a partition and its clusters: application to symbolic data sets., in E. Diday (Editor), M. Noirhomme-Fraiture (Co-Editor), Symbolic Data Analysis and the SODAS Software., Chichester: Wiley, p. 263-278
Brucker F., Bertrand P. (2007), On Lower-Maximal Paired-Ultrametrics, in Brito, P., Cucumel, G., Bertrand, P., De Carvalho, F., Selected Contributions in Data Analysis and Classification, Berlin: Springer, p. 455-464
Bertrand P., Csernel M. (2007), Sanskrit Manuscript Comparison for Critical Edition and Classification, in Brito, P., Cucumel, G., Bertrand, P., De Carvalho, F., Selected Contributions in Data Analysis and Classification, Berlin: Springer, p. 557-566
Trousse B., Bertrand P., Chelcea S. (2005), A New Agglomerative 2-3 Hierarchical Clustering Algorithm, in Baier D., Wernecke, K.-D., Innovations in Classification, Data Science, and Information Systems, Berlin: Springer, p. 3-10
Bertrand P., Goupil F. (2000), Descriptive Statistics for Symbolic Data, in Bock, H.-H. & Diday, E., Analysis of Symbolic Data, Exploratory methods for extracting statistical information from complex data, Berlin: Springer, p. 106-124
Bertrand P. (1995), Structural Properties of pyramidal clustering, in Cox, I., Hansen, P., Julesz, B., DIMACS Series in Discrete Mathematics and Theoretical Computer Science, 19 American Mathematical Society, p. 35-53
Communications avec actes
Essoussi N., Bertrand P. (2010), Kernel Overlapping K-Means for Clustering in Feature Space, in Fred, Ana L.N., Filipe, Joachim, KDIR 2010 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval, Valencia, Spain, October 25-28, 2010, Valence, SciTe Press, 250-255 p.
Communications sans actes
Bertrand P., Diatta J. (2023), Classifications multi-niveaux et convexités d’intervalle : cas de la hiérarchie du lien simple, Conférences PFIA’2023 (Plate-Forme Intelligence Artificielle), Strasbourg, France
Bertrand P., Diatta J. (2022), Hierarchies and Weak-hierarchies as Interval Convexities, 17th Conference of the International Federation of Classification Societies, Porto, Portugal
Bertrand P., Diatta J. (2019), Hiérarchies, hiérarchies faibles et convexités d’intervalle, 26 ème Rencontres de la Société Francophone de Classification, Nancy, France
Bertrand P., Diatta J. (2018), Classification multi-niveaux et convexité généralisée, XVèmes Rencontres de la Société Francophone de Classification, Paris, France
Bertrand P., Diatta J. (2014), Convexités d'intervalle et systèmes de classification, 21ièmes Rencontres de la Société Francophone de Classification, Rabat
Bertrand P., Diatta J. (2012), Séparation ternaire et propriété de convexité des structures de classification, XIXèmes Rencontres de la Société Francophone de Classification, Marseille
Présentation(s) dans un séminaire de recherche
Bertrand P. (2023), Classifications multiniveaux et convexités d’intervalle : Applications et discussion, in Séminaire du LIS, Marseille
Prépublications / Cahiers de recherche
Bertrand P., Diatta J. (2022), An interval convexity-based framework for multilevel clustering with applications to single-linkage clustering, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 33 p.
De A. T. De Carvalho F., Bertrand P., De Melo F. (2012), Batch self-organizing maps based on city-block distances for interval variables, Paris, Université Paris-Dauphine, 15 p.
Bel Mufti G., El Moubarki L., Bertrand P. (2012), Decomposition of the Rand index in order to assess both the stability and the number of clusters of a partition, Paris, Université Paris-Dauphine, 22 p.
Bertrand P. (2002), Set systems for which each set properly intersects at most one other set - Application to pyramidal clustering, Paris, Cahiers du CEREMADE
Bertrand P., Bel Mufti G. (2001), Stability of individual clusters, Cahiers du CEREMADE, 16 p.
Editoriaux, directions de revue
Saporta G., Bertrand P. (2008), Some Recent Trends in Applied Stochastic Modeling and Multidimensional Data Analysis - Editorial, Computational Statistics & Data Analysis, vol. 52, n° 6, p. 3164–3166