Collection 2022 - T3 - WS1 - Non-linear and high dimensional inference
In statistical learning and modern statistics, it is usually assumed that although data is observed in very high dimension, it actually live on — or near — a geometric structure of low dimension. The knowledge of such a low-complexity structure is of fundamental importance to improve both theoretical and computational aspects of a learning procedures.
Appears in collection : 2022 - T3 - Geometry and statistics in data sciences
Organizer(s) Aamari, Eddie ; Aaron, Catherine ; Chazal, Frédéric ; Fischer, Aurélie ; Hoffmann, Marc ; Le Brigant, Alice ; Levrard, Clément ; Michel, Bertrand
Date(s) 03/10/2022 - 07/10/2022
linked URL https://indico.math.cnrs.fr/event/7545/
