Autumn School on Constrained Optimization and Machine Learning

The Research Training Group on Algorithmic Optimization proudly announces its eighth Autumn School from October 9 – 11, 2024.

This year’s focus will be on 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.

Confirmed Speakers:

Emilio Carrizosa (University of Sevilla) – Mathematical Modeling for Counterfactual Explanations and Inverse Optimization

Tim Hoheisel (McGill University) – Regularized Least-Squares: Stability Properties and the Maximum Entropy of the Mean Method

Andrea Lodi (Cornell University) – Machine-Learning-Augmented Mixed-Integer Programming

Organizers:

Jan Pablo Burgard (Trier University)

Martin Schmidt (Trier University)

Volker Schulz (Trier University)

Schedule, Location and Travel Information: 

Schedule can be downloaded here.

The workshop will take place in Building E located on Campus I at Trier University.
For travel tips on how to get to Trier, please check  here;
Instructions on how to find Campus I are located here.

Registration information (registration is closed)

The registration fee of 60 € includes a welcome reception, the conference dinner, refreshments, and extra-curricular activities. Detailed payment information will be communicated upon registration. 

Travel Stipend (application is closed)