[Opt-Net] Autumn School on Constrained Optimization and Machine Learning

[Martin Schmidt]

The Research Training Group "Algorithmic Optimization" at Trier University proudly announces its 8th autumn school taking place October 9–11, 2024.

This year's focus will be on the intersection of constrained optimization and machine learning.

In today's rapidly evolving technological landscape, the intersection of constrained optimization and machine learning is gaining immense significance. As we tackle intricate real-world challenges, the synergy between these two domains gets more and more important. While unconstrained optimization methods have predominantly been employed in machine learning so far, constraints are becoming prevalent in a wide array of applications. This school offers a unique opportunity to deepen comprehension and delve into the latest advancements at the interface of the two fields. Thus, participants will acquire invaluable skills to confront the challenges of tomorrow.

The confirmed lecturers of this school are Emilio Carrizosa (University of Sevilla), Tim Hoheisel (McGill University), and Andrea Lodi (Cornell University).

All further information and the registration form can be found at https://alop.uni-trier.de/event/autumn-school-on-constrained-optimization-and-machine-learning/.