MA-INF 1218: Algorithms and Uncertainty


  • Next semester, we will offer a seminar and a lab on topics in the area of Algorithms and Uncertainty. You will also be able to propose your own topic ideas. Please contact Thomas Kesselheim if you are interested in participating in either or both.
  • There will also be the lecture Algorithmic Game Theory and the Internet, which has some similarities to this semester's lecture.

Scheduling Exams

To schedule the exam, please send an e-mail to Thomas Kesselheim.


When Where Start Lecturer
Tuesday, 14:15-15:45
Thursday, 14:15-15:45
CP1-HSZ / HS 3
CP1-HSZ / HS 3
October 9th Kesselheim


When Where Start Lecturer
Wednesday, 10:15-11:45 2.050 October 24 Kesselheim
Thursday, 10:15-11:45 2.050 October 25 Kesselheim


In many application scenarios, algorithms have to make decisions under some kind of uncertainty. This affects different kinds of problems. For example, when planing a route, a navigation system should take into consideration the traffic. Also, any machine-learning problem is about some kind of uncertainty. A random sample of data is used as a representative for the entire world.

In this course, we will get to know different techniques to model uncertainty and what approaches algorithms can use to cope with it. We will cover topics such as

  • Online Algorithms
  • Online Learning Algorithms and Online Convex Optimization
  • Sample Complexity
  • Markov Decisions Processes
  • Stochastic and Robust Optimization


You should bring a solid background in algorithms, calculus, and probability theory. Specialized knowledge about certain algorithms is not necessary.

Lecture Notes


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