Due to the situation imposed by COVID-19, the committee is evaluating periodically the situation and has already decided to postpone the registration after mid-May.
Aims of the iTWIST workshop series
The advent of increased computing capabilities, along with recent theoretical and numerical breakthroughs in the fields of signal processing, computational harmonic analysis, inverse problem solving, high-dimensional statistics and convex optimization, have boosted interactions between low-complexity data models (e.g., sparse or low-rank data models) and novel data sensing techniques.
In a nutshell, low-complexity data models aim at capturing, modeling and exploiting “just the information you need” in the ubiquitous data deluge characterizing any scientific or technological achievements. High dimensional objects can be thus reconstructed using little information. However, further developments and novel ideas are still required to meet new challenges, especially for efficiently dealing with complex data structures of “real life” applications and for interconnecting such models with other theoretical and applied fields.
The iTWIST workshop aims at fostering collaboration between international scientific teams for developing new theories, applications and generalizations of low-complexity models. This is why this event emphasizes dissemination of ideas through both specific oral/poster presentations and free discussions.
For this edition, iTWIST will be divided into two parts, a 2-day doctoral school, followed by the actual workshop for three days.