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 eight work groups that are headed by their respective group leaders:
We are pleased to announce that three papers by members of the Data Mining and Machine Learning research group are being presented at the 2026 …
We are pleased to announce that four papers have been accepted at the Conference on Neural Information Processing Systems (NeurIPS 2026).
We are pleased to announce that our paper has been accepted to IEEE International Conference on Data Mining (ICDM 2026).
