Advanced Machine Learning

Deductive logic is the tool of choice when premises are or are not true. This seminar will focus on a generalization of logic when the aim is to maximize our expected utility in cases where a premise holds only with a certain probability.

In other words, we will study how to make optimal decisions under uncertainty. This relates to important problems in reinforcement learning, control theory and game theory.

Literature: David Barber, Bayesian Reasoning and Machine Learning


On Tuesday, Oct 18th 2016, I will give general guidelines on "how to give a talk", and will outline the different topics. To choose a topic, you must be present on that occasion.

If you join, you will conduct a literature search on your topic, give a 45 min talk and summarize its contents in a report. You will receive 6 ECTS points and a grade based on: content of your talk (1/3), presentation (1/3) and quality of your report (1/3). This is a "Pflichtseminar" that is eligible towards the specialization in Computational Physics.

If you wish to participate, please send an email to lab manager Barbara Werner First come, first serve. If you have previously sent me an email, please forward your original message to the above address.


Tuesdays at 14:00, in the large seminar room, 3rd floor of HCI: Berliner Strasse 43.