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.