Statistical Machine Learning (Summer term 2026)

News / Quick links

  • Ilias
  • Register for exams! You need to register for the exam on Alma, deadline is one week before exam takes place. If you are not registered, you will NOT be able to participate in the exam. If for some reason you cannot register on Alma, please send an email to Patrizia Balloch to register (Subject: SML exam registration; Body: your name, degree program, matriculation number, and why you could not register on Alma).
  • Rough schedule for the end of term:
    • Week July 6: last assignment, last mandatory tutorial, normal lectures.
    • Week July 13: Mock exam comes out; no tutorials; no lecture on tuesday Jul 14 (instead: Machine Learning for Science Conference). Normal lecture on July 16
    • Week July 20: voluntary tutorials about mock exam; perhaps one last lecture on tuesday about research in Tuebingen, questions around doing a PhD, etc; definitely no lecture on thursday.
    • Week July 27: Exam takes place: July 28, 15:30-17:30, Lecture hall N6, Morgenstelle
  • Exam material The exam material will cover everything that was in the lecture except the legal part at the very end.

Slides


Some old slides, not used in this lecture but perhaps interesting:

Assignments

Exam modalities

Exam dates First exam is July 28, 15:30-17:30, Lecture hall N6, Morgenstelle
Second exam: October 8, 10:30-12:30, Lecture hall N6, Morgenstelle
The dates have been fixed by a central process. You can choose which exam to take, both will have the same difficulty. But note that there won't be a third exam nor oral exams: if you skip the first exam and fail the second one, you would need to wait for next summer term to take the exam again.

Exam admission To be admitted to the exam you need to need to achieve at least 50% of the points in the homework assignments, AND you need to attend at least 8 out of 11 tutorial sessions in person (documented by your signatures). If you have already tried the exam 2025 and failed, you can take the exam this year without earning a new exam admission (but we advise you do it, as it will prepare you for the exam). Exam admissions of 2024 or earlier are no longer valid.

Exam registration You need to register to the exam on Alma, the deadline is one week before the exam takes place. You cannot take part in the exam if you haven't registered!!! If for some reason, Alma doesn't let you register for the exam, please send an email to Patrizia Balloch with Ulrike Luxburg in cc, subject: Registration SML exam. Say that you would like to register, we need your name, your matriculation number, and the degree program in which you are enrolled.

Exam material You are not allowed to bring any material (books, slides, etc) except for what we call the controlled cheat sheet: one side (A4, one side only) of handwritten (!) notes, made by yourself. We will collect the notes at the end of the exam.

Day of the exam Please be there 15 min earlier and bring student ID or passport.

Online feedback form

We want to know what you like / do not like about the lecture! You can tell us anonymously with the following feedback form. The more concrete and constructive the feedback, the higher the likelihood that we can adapt to it.

Start-of-term-FAQ

  • Q: Do I need to register? A: Yes, on the Ilias platform, here is the registration link.
  • Q: Some of the material is password-protected. A: yes, you will get the password in the first lecture.
  • Q: I am an exchange student, or a student from a different degree program. Can I take part? A: Yes, if you have enough background knowledge. Q: How do I know? A: if in doubt, please approach me at the end of the first lecture (not by email).
  • Q: Can I participate remotely? A: No, the lectures will not be streamed / recorded, and attendance in the weekly tutorials is mandatory.
  • I have another question ... Ideally, please ask me at the end of the first lecture. Please don't send lots of questions by email.

Setup

What: Statistical Machine Learning, 9 CP
Lecturer: Prof. Ulrike von Luxburg
When and where: Lecture takes place Tuesdays and Thursdays 8:15 - 9:45, lecture hall A2, ground floor, Maria-von-Linden-Strasse 1. First lecture is on April 14. Tutorials: start in the second week of term.

Background information

This course is intended for the students of the master programs in machine learning or computer science or related degrees. It requires a solid understanding of maths, for example as taught in the course on Mathematics of Machine Learning: Linear algebra, Mulitvariate analysis, Probability Theory, Statistics, Optimization. The course is not recommended for students without this background. We also assume that students can program in python.

This lecture is going to be substantially revised and the contents shift quite a bit, compared to the last time I taught it. While the old lecture notes and the old videos still exist, you need to use the new lecture notes and attend the lectures in person to get the new content. The exam will be about the new content of course.

Info sheet about the logistics of the lecture: link

Registration

You need to register for this class on Ilias: registration link.

Tutorials

We will have weekly tutorial sessions, you will be assigned to one of the following groups: The teaching assistants are: The group assignments are kept up to date in Ilias. All groups are roughly at capacity. To switch group you first have to find switching partners from one of the other groups. Do NOT contact us before you tried finding a switching partner yourself.