Teaching

Winter term 2018/19

• Algorithms (Bachelor CS, 4+2 SWS)
• Statistical Network Analysis (Master CS, 2+2 SWS, by Debarghya Ghoshdastidar)
• Research seminar "Machine Learning Theory" (runs constantly)

Bachelor or Master theses

How to write a Bachelor or Master thesis in our group:

• General information and first steps
• List of topics (login and password required, same as for all my lectures)
• Tips about how to actually write the thesis.

Credits for courses taken at other universities (Anerkennung von Pruefungsleistungen)

I am dealing with these issues just in the context of Mathematics 1 to 3. Please do the following:

• Bachelor/Master Informatik: bitte Unterlagen wie hier beschrieben einreichen (nicht bei mir!)
• Master Medieninformatik: bitte schicken Sie mir alle Unterlagen als ein pdf (!)-Dokumente per email: Was wollen sie wofür anerkennen lassen / bestätigt bekommen (welcher vorige Studiengang, welche Veranstalung); Zusammenfassung der Inhalte Ihrer besuchten Veranstaltung, zum Beispiel Auszug aus Modulhandbuch; Bestätigung, dass Sie die Veranstaltung bestanden haben, zum Beispiel transcript of records). Dann schaue ich mir die Sachen in Ruhe an und melde mich wieder bei Ihnen.

FAQ and HOWTO pages

• Exams: FAQ and how to prepare
• Seminars: how to prepare

Consultation hour / Sprechstunde

I do not have a fixed time. Please send an email in which you explain why you want to talk to me, then we can make an appointment. Please do not just drop in my office unless it is really urgent.

Feedback Form

In case you want to send us anonymous feedback about one of our lectures or seminars, you can use our online feedback form.

Past lectures and seminars

• Summer term 2018:
  • Machine Learning: Algorithms and Theory (4 + 2 SWS), lecture course for Master Students
  • Seminar Statistical Inference on Networks for Master students (2 SWS), taught jointly with Debarghya Ghoshdastidar
• Winter term 2017/18
  • Mathematik 1 for Bachelor Students (Bachelor CS, 4+2 SWS).
  • Seminar Ethik und Wissenschaftstheorie des maschinellen Lernens, joint seminar by Thomas Grote (Ethics), Philipp Berens, Ulrike von Luxburg, for Master students of diverse disciplines.
• Summer term 2017 Machine learning: theory and algorithms (Master students CS + Maths, 4+2 SWS).
• Winter term 2016/17
  • Mathematik 1 for Bachelor Students (Bachelor CS, 4+2 SWS)
  • Seminar: Machine Lerning Theory: Crowdsourcing algorithms and their statistical analysis (Master CS)
• Summer term 2016: Machine learning: algorithms and theory (Master CS and Maths, 4 + 2 SWS)
• Summer 2015: Statistical Learning Theory, course for the machine learning summer school, Tuebingen, Germany.
• Summer term 2015: Machine learning (Master CS and Maths, 4 + 2 SWS).
• Winter term 2014/15: Algorithms and Data Structures (Bachelor CS, 3+1 SWS)
• Summer term 2014: Machine learning (Master CS and Maths, 4 + 2 SWS).
• Winter term 2013/14: Algorithms and Data Structures (Bachelor CS, 3+1 SWS)
• Mathematical Theory of Machine Learning (Master Maths and CS, 2 SWS)
• Summer term 2013: Machine learning / algorithmic learning (Master CS and Maths, 4+2 SWS)
• Winter term 2012/13: Advanced algorithms (Master CS, 4+2 SWS)
• Summer term 2012: Seminar Machine Learning (Master CS, 2 SWS)
• Winter term 2011/12: Advanced Algorithms (Master CS, 4+2 SWS)
• Summer term 2011: "Unsupervised learning and the analysis of networks" (Master CS, 2+2 SWS)
• Winter term 2007/2008: "Mathematical theory of machine learning" at the Mathematics Department of the University of Tübingen
• Summer 2007: Course on "Clustering: Theory and Algorithms" at the Pascal Machine Learning Bootcamp, Barcelona, Spain
• Summer 2007: Practical Sessions on "Spectral Clustering and other graph based algorithms" at the Machine Learning Summer School, Tübingen, Germany. Matlab Graph Demo available here.
• Summer term 2006: "Unsupervised Learning", TU Darmstadt
• Winter term 2005/06: Seminar Machine Learning with Graphs, TU Darmstadt