Structured data analysis

Arthur Tenenhaus (CentraleSupelec, Laboratoire des Signaux et Systèmes, France)
February 13, 2015 — 10:30 — "None"

Abstract

In contrast to standard data that is structured by a single individuals variables data matrix, structured data are characterized by multiple and heterogeneous sources of information, interconnected, potentially of high dimensions. In addition, each source of information may also have a complex structure (e.g. tensor structure). The need to analyze the data by taking into account their natural structure appears to be essential but requires the development of new statistical techniques that constitute the core of my current research for many years. More specifically, I will present a unified framework for multiblock, multigroup and multiway data analysis through Regularized Generalized Canonical Correlation Analysis.