Mathematics, Signal Processing and Learning

Mathématiques, traitement du signal et apprentissage​

HYBRID RESEARCH SCHOOL  / 25 – 29 January 2021
(Marseille, France local time)

This week will consist of a doctoral school on mathematics and learning with an emphasis on signal and image processing. The main topic will be the basics of learning, plus more advanced classes on reinforcement learning and deep learning for example, as well as classes on signal processing and optimization in machine learning. Most of the lectures will adopt a mathematical view of machine learning and will feature practical sessions (for example in Python). Finally, the participants will also have the opportunity to present their work in poster or short oral sessions.

Organizing Committee

Sandrine Anthoine (CNRS – Aix-Marseille Université)
Caroline Chaux (CNRS – Aix-Marseille Université)
Hachem Kadri (Aix-Marseille Université)
Frédéric Richard (Aix-Marseille Université)

Scientific Committee

Francis Bach (INRIA Paris)
Richard Baraniuk (Rice University)
Gabriel Peyré (CNRS – ENS Paris)

Discussion rooms will be available to registered research school participants via the link below. Your access code to the rooms is provided by the organizers.
This page is accessible with a password issued by CIRM.

Use of Big Blue Button


  • Basics of learning:

Marianne Clausel (Université de Lorraine)

  • Signal processing:

Nicolas Vayatis (ENS Paris-Saclay), Laurent Oudre (ENS Paris-Saclay)

  • Optimization:

Nelly Pustelnik (CNRS, ENS Lyon)

  • Reinforcement learning: 

Allesandro Lazaric (Facebook AI Research)

  • Deep learning:

Edouard Oyallon (LIP6, CNRS)