Part 5: Convex Problems

Several methods have been tailored to non-smooth convex problems. We discuss how they balance stronger assumptions with better performance.

Short bio:

Alberto De Marchi is a Postdoctoral Research Associate at the Institute of Applied Mathematics and Scientific Computing, University of the Bundeswehr Munich (Germany), where he received his PhD in 2021. He obtained an M.Sc. in Mechatronics Engineering from the University of Trento. He was awarded the 2022 Best Paper Prize in Computational Optimization and Applications. His research focuses on the design and analysis of computational tools for mathematical optimization problems.