logo Lille1 October 7th 2016

Learning with functional data

There are no fees, but registration is mandatory (Lunch is offered to participants).

Location: Amphi 1A06, IUT "A" ( ➜ access)

Short description: Fonctional data are present in many domains: image observation across the time, weather data on several variables collected from balloons, medical state of a patient over the time,… These functional data can be of different type (quantitative or qualitative) and be univariate or multivariate. The statisticians when dealing with such type of data has generally the same aim as with vector data: make supervised or unsupervised clustering, make dimension reduction, use linear models.
The workshop presents a large scope of methods for learning with functional data with application to various domains.

Keywords: Supervised Clustering, Spectrometry, Learning, Kernels, Missing Values.

Invited (and confirmed) speakers:
  • Sophie Dabo-Niang
  • Julien Jacques
  • Valérie Monbet
  • Cristian Preda
  • Frédéric Ferraty
  • Hachem Kadri
  • Rémi Servien
Organizers: S. Iovleff, C. Preda, V. Vandewalle, S. Girard, M. Fauvel.