| Time/Place: | Wednesday 10-12 a.m., SR 226, Hermann-Herder-Str. 10 |
| Lecturer: | Prof. Dr. Sören Bartels |
| Office hour: | Tue 12-1 p.m., Room 209, Hermann-Herder-Str. 10 |
| Exercises | Tatjana Schreiber |
| Office hour: | at any time by appointment, Room 211, Hermann-Herder-Str. 10 |
| E-Mail: | tatjana.stiefken@mathematik.uni-freiburg.de |
The lecture addresses algorithmic aspects in the practical realization of mathematical methods in big data analytics and machine learning. The first part will be devoted to the development of recommendation systems, clustering methods and sparse recovery techniques. The architecture and approximation properties as well as the training of neural networks are the subject of the second part. Convergence results for accelerated gradient descent methods for nonsmooth problems will be analyzed in the third part of the course. The lecture is accompanied by weekly tutorials which will involve both, practical and theoretical exercises.
Numerik I, II or Basics in Applied Mathematics
Hand in your solutions to the letterbox on the second floor of the Rechenzentrum (mailbox 8). You can submit your solutions in teams of two.
| Exercise Sheet | Start Date | Submission Date |
| Sheet 1 | 23.04.2025 | 02.05.2025, 2 p.m. |
The tutorial starts in the second week of lectures.
| Group | Tutor | Time/Place |
| 1 | Nathalie Janes (nathalie.janes@email.uni-freiburg.de) | Wednesday, 2-4 p.m./ SR 318 |
