The research group Data Mining and Machine Learning investigates novel approaches to exploratory data analysis, unsupervised, semi-supervised and supervised learning. We focus on methods for various data types including texts, graphs, high-dimensional feature vectors and other complex structures. We consider different tasks, e.g., representation learning, embedding, clustering, causality detection, classification and reinforcement learning.

The research group Data Mining and Machine Learning consists of four work groups:

Our methods are inspired by challenges arising from different application areas, e.g. medicine, neuroscience, pharmacoinformatics, renewable energies and social sciences.

Team of research group DM

Publications of research group DM

Projects of research group DM


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Paper accepted at IJCAI 2022

Our paper "Option Transfer and SMDP Abstraction with Successor Features" has been accepted at the International Joint Conference on Artificial Intelligence (IJCAI)

Paper accepted at The Web Conference 2022

Our paper "Temporal Walk Centrality: Ranking Nodes in Evolving Networks" has been accepted at The Web Conference 2022

Paper accepted to AAAI2022

Our paper "Causal Discovery in Hawkes Processes by Minimum Description Length" has been accepted to AAAI2022.

Franka Bause receives Hans Uhde Award

The Hans Uhde Prize is awarded to the best students of the TU Dortmund

University for outstanding theses in engineering. Congratulations, Franka!

Review of the Kaiserschild Lectures with Prof. Claudia Plant "AI in Medicine" [german]

On 15 April, experts discussed the question of whether artificial intelligence can revolutionise medicine as part of the Kaiserschild Lectures series. Among the panelists:...

Wir freuen uns Benjamin Roth an unserer Fakultät willkommen zu heißen. Die neugeschaffene Professur "Digitale Textwissenschaften" ist an der Fakultät für Informatik und der...

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