The importance of high-dimensional data stands in their ability to store a wide range of complex information, pivotal across various fields such as genetics, economics, and meteorology. The inherent complexity of these datasets necessitates new statistical methods and advanced algorithms to effectively manage and interpret them. This workshop will highlight these challenges and present state-of-the-art methodologies and theoretical advances tailored specifically to high-dimensional time series.
--- INVITED SPEAKERS Marc Hallin (Université Libre de Bruxelles), Marco Lippi (Einaudi Institute for Economics and Finance (EIEF)), Tommaso Proietti (University of Rome Tor Vergata), Alessandro Razeto (INFN - LNGS)
