Great Ideas in Learning and Control
Many of the great ideas that shaped today’s fields of machine learning and control theory were developed in the 20th century. These ideas established the theoretical and conceptual foundations for how systems can learn, adapt, and make decisions. They had a profound impact on engineering, science and society throughout the past century. In this course, we will explore these some foundational concepts and their influence on modern learning and control.
Lectures
| Lecture | Date | Room |
|---|---|---|
| L1 Principles of information theory | 17th Feb @ 10.15 | 101127, Ångström |
| L2 Principles of dynamical systems | 24th Feb @ 10.15 | 101258, Ångström |
| L3 Principles of extremum problems | 3rd Mar @ 10.15 | 101125, Ångström |
| L4 Principles of feedback | 10th Mar @ 10.15 | 101125, Ångström |
| L5 Principles of statistical learning | 17th Mar @ 10.15 | 101125, Ångström |
| L6 Principles of dynamic programming | 24th Mar @ 10.15 | 101125, Ångström |
Examination
- Write a brief reflection for each lecture.
- A collaborative project.
Questions and Registration
If you want to register for the course fill in this form.
PhD students that finish the course receive 5 credits, but anyone is welcome to attend. If you have questions you can e-mail Dave Zachariah or Per Mattsson.