Machine Learning research unit

Welcome to the web-home of the new Machine Learning research unit of TU Wien Informatics. Our physical home is on Campus Gusshaus (CA03).

Our research aims to narrow the gap between theoretically well-understood and practically relevant machine learning. Research questions concern for instance:

• learning with non-conventional data, i.e., data that has no inherent representation in a table or Euclidean space
• incorporation of invariances as well as expert domain knowledge in learning algorithms
• computational, sample, query, and communication complexity of learning algorithms
• constructive machine learning scenarios such as structured output prediction
• learning with small labelled data sets and large unlabelled data sets
• adversarial learning with mistake and/or regret bounds
• parallelisation/distribution of learning algorithms
• approximation of learning algorithms
• scalability of learning algorithms
• reliability of learning algorithms
• extreme learning
• ...

To demonstrate the practical effectiveness of novel learning algorithms, we apply them in Chemistry, Material Science, Electrical Engineering, Computer Games, Humanities, etc.