Multi-Agent Optimization and Learning

This website serves as a companion to the “Multi-Agent Optimization and Learning” short-course at IEEE ICASSP 2024. Our objective is to provide attendees with tools for distributed optimization and learning that allow them to design intelligent distributed systems. Emphasis is placed on why algorithms work, how we can systematically develop them, and how we can quantify their performance trade-offs. We also show how to use this information to drive design decisions.

In the top-right corner, you will find a lectures tab, which contains slides and notes for each individual lecture. The labs tab contains computer exercises in the form of Jupyter notebooks.

Please contact the instructors per email with any questions or comments regarding the material. Feedback is very much appreciated.