"Research school - Mathematics, Signal Processing and Learning"
25-29 Jan. 2021


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.


Registration is free but mandatory.

Links to lectures

Five lectures:

Links to practical sessions

Links to teasers

Eleven two minutes teasers:

Links to posters

Let's meet here !
  1. Safaa Al Ali - Automatic detection of ulcerative colitis lesions in colonoscopy videos (Poster)
  2. Pierre Louis Antonsanti - Partial Shape Matching in the Space of Varifolds (Poster)
  3. Andre Belotto - An ODE to Model First-Order Adaptive Algorithms (Poster)
  4. Cyril Cano - Gravitational-wave polarimetry with quaternions and application to precessing binaries (Poster)
  5. Jeremy Cohen - Convolutive semi-supervised beta-NMF for automatic music transcription (Poster)
  6. Cyprien Doz - Large dimensional analysis of LS-SVM transfer learning: Application to POLSAR classification (Poster)
  7. Marta Lazzaretti - Weighted-CEL0 sparse regularisation for molecule localisation in Super-Resolution microscopy with Poisson data (Poster)
  8. Yusuf Ygit Pilavci - Smoothing graph signals via random spanning forests (Poster)
  9. Willy Rodriguez - Computing document distances using optimal transport (Poster)
  10. Vasiliki Stergiopoulou - COL0RME: COvariance-based l0 super-Resolution Microscopy with intensity Estimation (Poster)
  11. Yacouba Kaloga - Multiview Variational Graph Autoencoders for Canonical Correlation Analysis (Poster)
  12. Zip file with all posters (zip)