Learning and Optimization in Luminy - LOL2022 / Apprentissage et Optimisation à Luminy - LOL2022

Collection Learning and Optimization in Luminy - LOL2022 / Apprentissage et Optimisation à Luminy - LOL2022

Artificial intelligence is now at the heart of society. While the empirical performance of the most recent machine learning techniques, such as deep neural networks, is undeniable, real theoretical questions are emerging and resonating in different mathematical communities. The aim of this conference is to bring together researchers from various specialties such as machine learning, statistical learning, but also optimization, computer science and statistical physics.

Three main themes have been identified:

(i) Stochastic optimization and collaborative learning. Stochastic optimization has become key to cope with the data deluge, and has undeniably deployed the power of neural networks. Stochastic optimization -of neural networks- has raised real theoretical questions, which put non-convex optimization to the test. On the other hand, collaborative learning consists in performing optimization tasks in a decentralized manner. Standard statistical techniques are no longer applicable as such, and must adapt to distributed or heterogeneous databases, with communication constraints between machines.

(ii) High-dimensional statistics. Sparse regressions, matrix completion or dictionary learning are instances of inverse problems, which have recently been challenged by the predictive capabilities of neural networks. This competition opens new avenues of reflection, and the reconstruction optimality of these two types of methods remains to be formalized and studied, especially in terms of stability and robustness.

(iii) Recent developments in machine learning: from theory to practice. If non-smooth or non-convex optimization still has several challenges to meet, it seems to us essential to bring together its best theorists as well as its best practitioners from the statistical and optimization sides.

The most influential and internationally recognized researchers in the different fields mentioned above will be invited to present their most innovative work. Finally, time slots will be specially dedicated to encourage the setting up of working groups.


Organizer(s) Boyer, Claire ; d'Aspremont, Alexandre ; Dieuleveut, Aymeric ; Moreau, Thomas ; Villar, Soledad
Date(s) 03/10/2022 - 07/10/2022
linked URL https://conferences.cirm-math.fr/2551.html
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