According to the No Free Lunch Theorem, we cannot expect a single method to perform well on every optimization problem instance or machine learning dataset. The Algorithm Selection Problem addresses how to determine which available algorithm is most appropriate for a particular instance or dataset. This course introduces key concepts in algorithm selection for optimization, explores automated machine learning, and discusses applications and recent advances in automated algorithm selection.
Nysret Musliu is with the Christian Doppler Laboratory for AI and Optimization in Planning and Scheduling at the Institute of Logic and Computation, Technische Universität Wien, Austria.
The course is organized in three sessions: