Teaching


Master 2 MVA

This is the homepage for my course in Master 2 Mathématiques, Vision, Apprentissage - MVA.

Description

Evolution of the course:

  • Since 2019: Computational Optimal Transport
  • 2017-2019: Mathematical Foundation of Data Sciences
  • 2008-2016: Sparsity and compressed sensing

The course presents an overview of the mathematics of data sciences. This includes in particular tools from convex optimization, compressed sensing and optimal transport. It showcases application in machine learning and imaging sciences.

Pre-requisite

Basics of linear algebra, calculus and Fourier transform.

Validation of the course

Attending all the numerical tours, a mini-project with a report and an oral presentation. Note that there is a special session dedicated to the preparation of the projects.

Ressources

Other MVA courses on the web