In recent years, in a wide range of scientific and technological domains, huge amount of data have been generated. This represents a great challenge in many cross-disciplinary fields.
Usually, data have a large number of dimensions, as well as of observations. They can be categorical, discrete, quantitative, and often data types are mixed.
This high dimensionality and different data types and structures make the traditional statistical methods unable to analyse this kind of data. The development of new data mining methods, such as multivariate data analysis, graphical models and data visualization tools present new challenges.
This workshop represents a venue to discuss recent development of algorithms, methods, applications and software for mining high dimensional data.
The Workshop is supported by the Italian Statistical Society, the Laboratory for Genomics, Transcriptomics and Proteomics of Italian National Reseach Council, and the group of "Data Mining et Apprentissage" of Société Française de Statistique.
Selected papers will be published in a volume.
Edwin Diday, Université Paris-Dauphine
Gilbert Saporta, CNAM – Paris
Michel Verleysen, Université Catholique de Louvain