iTWIST 2020 - online from Centrale Nantes
iTWIST 2020 (International Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques) will be held online with a two-day doctoral school followed by three days of workshop.
From November 30, 2020 to December 4, 2020 All day
The iTWIST workshop aims at fostering collaboration between international scientific teams for developing new theories, applications and generalizations of low-complexity models. For this edition, iTWIST will be divided into two parts, a 2-day doctoral school (30 November - 1 December) followed by the workshop over three days (2 - 4 December).
Due to the coronavirus pandemic, the doctoral school and the workshop will take place entirely online (Zoom links on the website).
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.
Due to the coronavirus pandemic, the doctoral school and the workshop will take place entirely online (Zoom links on the website).
About iTWIST
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.
- Learn more: https://itwist20.ls2n.fr
Organising Committee
- Sébastien Bourguignon (Centrale Nantes, LS2N, Nantes, France)
- Cédric Herzet (INRIA Rennes, France)
- Jérôme Idier (CNRS, LS2N, Nantes, France)
- Charles Soussen (CentraleSupélec, L2S, Gif-Sur-Yvette, France)