July 1, 08:30 to July 3, 2024, 17:00
Institut de Mathématiques de Toulouse
Room Amphithéatre Schwartz, Institute of Mathematics of Toulouse, Université Paul Sabatier.
The program of the workshop and (most of) the abstracts are online.
Regret-based learning algorithms have found applications in various environments including stochastic, adversarial and multi-agent ones. While optimal convergence rates were known in the stochastic and adversarial settings, the corresponding results in the multi-agent settings have started to appear only recently.
The aim of this workshop is to showcase recent trends and advances in regret-based learning algorithms in multi-agent competitive environments.
The program will consist of two tutorials, 15 invited talks, and poster presentations. For participants interested in presenting their work in the form of a poster and a flash-talk, the call for posters has all the details including the possibility of applying for a grant.
This workshop is part of the thematic semester Stochastic control and learning for complex networks (SOLACE) funded by Labex CIMI.
